subject:( en GENETIC ALGORITHMS)

Pontifical Catholic University of Rio de Janeiro

1. RENE GONZALEZ HERNANDEZ. [en] RESOURCE OPTIMIZATION FOR ELECTIVE SURGICAL PROCEDURES USING QUANTUM-INSPIRED GENETIC ALGORITHMS.

Degree: 2019, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=37529

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[pt] Atualmente as Unidades de Saúde, em um grande número de países do mundo, apresentam demandas de serviços que superam suas capacidades reais. Por esta… (more)

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[pt] Atualmente as Unidades de Saúde, em um grande número de países do mundo, apresentam demandas de serviços que superam suas capacidades reais. Por esta razão, o surgimento das listas de espera é inevitável. Preparar o planejamento das mesmas, de modo otimizado resulta, portanto, em um grande desafio, devido à quantidade de recursos que devem ser considerados. O caso particular dos procedimentos cirúrgicos é particularmente crítico pela quantidade de recursos que se precisam para a realização do mesmo. Poucos projetos têm sido desenvolvidos para a gestão completa dessas listas. O trabalho desenvolvido nesta Dissertação propõe o uso de um modelo, baseado em algoritmos genéticos com inspiração quântica, para a automatização e otimização do planejamento de procedimentos cirúrgicos eletivos. Este modelo, denominado Algoritmo Evolucionário com Inspiração Quântica para a Área de Saúde (AEIQ-AS), além de alocar os pacientes e os recursos necessários para que o processo cirúrgico seja exitoso, procura reduzir o tempo total para que todas as cirurgias sejam realizadas. Este trabalho apresenta também uma ferramenta que permite a modelagem, de modo simplificado, de uma Unidade Cirúrgica de Saúde. Esta ferramenta possibilita a realização de simulações com o objetivo de ver o efeito de diferentes configurações dos recursos nas Unidades de Saúde. Para a validação do modelo proposto foi criada, de modo artificial e fazendo uso da ferramenta de simulação, uma lista de espera de 2000 cirurgias. Caso as cirurgias fossem realizadas seguindo a ordem de chegada, seriam necessárias pouco mais de 37 semanas e teria 1066 operações fora do prazo. Foram feitos vários experimentos onde se buscava a otimização destes valores. Esta busca foi feita, primeiramente, tomando em consideração só um dos parâmetros e a continuação eles em conjunto. Na primeira abordagem o AEIQ-AS consegue a realização das mesmas cirurgias em aproximadamente 31 semanas. Assim, observa se que há uma redução de aproximadamente 16,25 porcento do tempo. O número de operações fora do prazo, por sua vez, foi reduzido pelo modelo para 927 (13,04 porcento). Na abordagem simultânea, o AEIQ-AS, consegue uma diminuição do tempo total de alocação em 16,22 porcento e o número de operações fora do prazo em 9,76 porcento. Foram feitas, também, várias simulações da Unidade de Saúde mantendo as caraterísticas da lista de cirurgias para ver seu efeito no tempo total de alocação de todos os processos cirúrgicos.

[en] Currently, Health Units in a large number of countries in the world present service demand that exceed their real capacities. For this reason, is inevitable the emergence of the waiting lists. To prepare the planning of this in an optimized manner results in a substantial challenge due to the number of resources that should be considered. The case of chirurgical procedures is particularly critical by the number of resources needed for their realization. A small quantity of projects has been developed to fully manage these lists. The work developed in this Dissertation…

Advisors/Committee Members: MARLEY MARIA BERNARDES REBUZZI VELLASCO.

Subjects/Keywords: [pt] OTIMIZACAO; [en] OPTIMIZATION; [pt] SAUDE; [en] HEALTH; [pt] ALGORITMOS GENETICOS; [en] GENETIC ALGORITHMS; [pt] ALGORITMOS GENETICOS COM INSPIRACAO QUANTICA; [en] GENETIC ALGORITHMS WITH QUANTUM INSPIRATION; [pt] SCHEDULE; [en] SCHEDULE

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

HERNANDEZ, R. G. (2019). [en] RESOURCE OPTIMIZATION FOR ELECTIVE SURGICAL PROCEDURES USING QUANTUM-INSPIRED GENETIC ALGORITHMS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=37529

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

HERNANDEZ, RENE GONZALEZ. “[en] RESOURCE OPTIMIZATION FOR ELECTIVE SURGICAL PROCEDURES USING QUANTUM-INSPIRED GENETIC ALGORITHMS.” 2019. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=37529.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

HERNANDEZ, RENE GONZALEZ. “[en] RESOURCE OPTIMIZATION FOR ELECTIVE SURGICAL PROCEDURES USING QUANTUM-INSPIRED GENETIC ALGORITHMS.” 2019. Web. 20 Jan 2021.

Vancouver:

HERNANDEZ RG. [en] RESOURCE OPTIMIZATION FOR ELECTIVE SURGICAL PROCEDURES USING QUANTUM-INSPIRED GENETIC ALGORITHMS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2019. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=37529.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

HERNANDEZ RG. [en] RESOURCE OPTIMIZATION FOR ELECTIVE SURGICAL PROCEDURES USING QUANTUM-INSPIRED GENETIC ALGORITHMS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2019. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=37529

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Satishkumar, M V. Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms.

Degree: 2010, Jawaharlal Nehru Technological University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/2255

► High degree of flexibility and quick response times have become essential features of modern manufacturing systems where customers are demanding for a variety of products… (more)

Subjects/Keywords: Genetic Algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Satishkumar, M. V. (2010). Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms. (Thesis). Jawaharlal Nehru Technological University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/2255

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Satishkumar, M V. “Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms.” 2010. Thesis, Jawaharlal Nehru Technological University. Accessed January 20, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/2255.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Satishkumar, M V. “Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms.” 2010. Web. 20 Jan 2021.

Vancouver:

Satishkumar MV. Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms. [Internet] [Thesis]. Jawaharlal Nehru Technological University; 2010. [cited 2021 Jan 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/2255.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Satishkumar MV. Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms. [Thesis]. Jawaharlal Nehru Technological University; 2010. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/2255

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

3. SAMUEL GUSTAVO HUAMAN BUSTAMANTE. [en] INVERSION OF GEOPHISYCS PARAMETERS IN THREE DIMENSIONS FROM SEISMIC REFLECTION DATA BY HYBRID GENETIC ALGORITHMS.

Degree: 2009, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13066

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[pt] Este trabalho tem por objetivo investigar um método para auxiliar na quantificação de características sísmicas do subsolo. O modelo sísmico bidimensional de reflexão usa… (more)

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[pt] Este trabalho tem por objetivo investigar um método para auxiliar na quantificação de características sísmicas do subsolo. O modelo sísmico bidimensional de reflexão usa a equação Normal Move Out (NMO), para calcular os tempos de trânsito das ondas sísmicas, tipo P, refletidas em camadas isotrópicas e inclinadas. Essa equação usa a velocidade raiz quadrática média RMS como valor representativo das velocidades intervalares das camadas unidas. No processo de inversão para múlltiplas camadas, as velocidades RMS representam o problema principal para estimar as velocidades intervalares. Conseqüentemente, o método proposto estima sequencialmente os parâmetros do modelo sísmico, para resolver esse problema a partir dos tempos de trânsito com Algoritmos Genéticos Híbridos (algoritmo genético e algoritmo Nelder Mead Simplex). Os tempos de trânsito são sintéticos e a estimação de parâmetros é tratada como um problema de minimização. Com o método proposto foi obtido um alto grau de exatidão, além de reduzir o tempo de computação em 98,4 % em comparação com um método de estimação simultânea de parâmetros. Para aliviar a complexidade e a demora na geração de um modelo em três dimensões se contrói um modelo sísmico em três dimensões formado com modelos bidimensionais, sob cada unidade retangular da malha de receptores do levantamento sísmico, para camadas isotrópicas curvadas, com variações suaves das pendentes e sem descontinuidades. Os modelos bidimensionais formam polígonos que representam as superfícies de interface que são projetadas sob os retângulos da malha. Dois conjuntos de superfícies poligonais são gerados para auxiliar na localização das camadas.

[en] The objective of the present work is to investigate a method to help in the quantification of seismic characteristics underground. The two-dimensional seismic model of reflection employs the equation Normal Move Out (NMO) to calculate the travel times of P waves reflected on inclined and isotropic layers. This equation uses the root mean square velocity as a representative value of the joined layers velocities. At the inversion process, for multiple layers, the root mean square velocities are the main problem to estimate the layer velocities. Consequently, to solve that problem, the proposed method estimates sequentially the parameters of the seismic model using travel times and the Hybrid Genetic Algorithms (Genetic algorithm and the Nelder Mead Simplex algorithm). The travel times are synthetic and the estimation of parameters is treated as a minimization problem. With proposed method was obtained high grade of accurate, and the reduction of 98.4 % of computing time when it was compared to a simultaneous parameters estimation method. For decreasing the complexity and the delay to generate the models in three dimensions is proposed the construction of a three-dimensional seismic model formed with two-dimensional models, under every rectangular cell of the mesh of receptors of the seismic survey, for curved isotropic layers with soft variations in the gradient…

Advisors/Committee Members: MARCO AURÉLIO CAVALCANTI PACHECO.

Subjects/Keywords: [pt] ANALISE DE VELOCIDADE; [en] VELOCITY ANALYSIS; [pt] PROJECOES ORTOGONAIS; [en] ORTHOGONAL PROJECTIONS; [pt] ALGORITMOS GENETICOS HIBRIDOS; [en] HYBRID GENETIC ALGORITHMS

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

BUSTAMANTE, S. G. H. (2009). [en] INVERSION OF GEOPHISYCS PARAMETERS IN THREE DIMENSIONS FROM SEISMIC REFLECTION DATA BY HYBRID GENETIC ALGORITHMS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13066

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

BUSTAMANTE, SAMUEL GUSTAVO HUAMAN. “[en] INVERSION OF GEOPHISYCS PARAMETERS IN THREE DIMENSIONS FROM SEISMIC REFLECTION DATA BY HYBRID GENETIC ALGORITHMS.” 2009. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13066.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

BUSTAMANTE, SAMUEL GUSTAVO HUAMAN. “[en] INVERSION OF GEOPHISYCS PARAMETERS IN THREE DIMENSIONS FROM SEISMIC REFLECTION DATA BY HYBRID GENETIC ALGORITHMS.” 2009. Web. 20 Jan 2021.

Vancouver:

BUSTAMANTE SGH. [en] INVERSION OF GEOPHISYCS PARAMETERS IN THREE DIMENSIONS FROM SEISMIC REFLECTION DATA BY HYBRID GENETIC ALGORITHMS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2009. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13066.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

BUSTAMANTE SGH. [en] INVERSION OF GEOPHISYCS PARAMETERS IN THREE DIMENSIONS FROM SEISMIC REFLECTION DATA BY HYBRID GENETIC ALGORITHMS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2009. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13066

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

4. LUIGI DE MAGALHAES DETOMI CALVETTE. [en] GENETIC ALGORITHMS AND REAL OPTIONS ON THE WILDCAT DRILLING OPTIMAL CHOICE.

Degree: 2015, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24204

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[pt] A exploração e desenvolvimento de um campo de petróleo é permeada de incertezas de diferentes naturezas. A incerteza mais básica que o gestor de… (more)

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[pt] A exploração e desenvolvimento de um campo de petróleo é permeada de incertezas de diferentes naturezas. A incerteza mais básica que o gestor de um portfolio exploratório enfrenta é aquela relativa à existência (ou não) de petróleo em determinado prospecto. Tipicamente, incertezas técnicas tendem a ser reduzidas com investimentos em aquisição de informação, que são exercícios de opções de aprendizagem. Decorrente da estrutura de correlações presentes nos prospectos de um portfolio exploratório, o resultado da perfuração de um poço pioneiro potencialmente irá revelar informações adicionais sobre a probabilidade de existência (ou não) de petróleo em outros prospectos deste mesmo portfolio. Cada poço a ser perfurado pode ser entendido como uma opção de aprendizagem a ser exercida (ou não) a depender da sua probabilidade de sucesso. Neste contexto, um dos fatores determinantes na otimização da campanha exploratória é a escolha da sequência ideal de perfuração de poços. Tal escolha é mais complexa, quão maior for a quantidade e diversidade de prospectos no portfolio. Diante dessa realidade, este trabalho propõe uma modelagem que busca, através de Algoritmos Genéticos, otimizar a sequência de perfurações dos poços e, portanto, o valor do portfolio. O modelo proposto considera as interdependências e as especificidades de cada prospecto e usa como função objetivo, a ser maximizada, o valor presente do líquido (VPL). Opções e aprendizagem são os aspectos-chave por trás do modelo de otimização. O modelo foi avaliado em dez diferentes portfolios exploratórios e, em todos os casos, foi capaz de propor pelo menos uma sequência que apresentasse expressivos ganhos de VPL em relação ao caso-base.

[en] An oil field exploration and development campaign is bounded with different kinds of uncertainty. The most basic one that an E and P portfolio manager deals with is the one related to the existence (or not) of oil in a given prospect. Typically, technical uncertainties are related to learning, and tend to be reduced with investments on information acquisition. From the correlation pattern on the prospects in a given exploratory portfolio, follows that the results from one initial wildcat drilling will, potentially, reveal, additional information about the oil existence (or not) in other prospects in the same geological play. This way, each prospect to be drilled might be understood as a learning option to be exercised (or not) depending on its respective success probability. In such case, one of the main factors on optimizing the exploratory campaign is choosing the ideal drilling sequence. Such choice is more complex, as the quantity and diversity of the prospects increases. Given such background, the present work proposes a model that intends, using Genetic Algorithms, to optimize the drilling sequence and, as a consequence, the total portfolio value. The proposed model considers the interdependencies and each prospect specific aspects and has as an objective function (to be maximizes) the portfolio net present value (NPV).…

Advisors/Committee Members: MARCO AURELIO CAVALCANTI PACHECO, MARCO AURELIO CAVALCANTI PACHECO.

Subjects/Keywords: [pt] OTIMIZACAO; [en] OPTIMIZATION; [pt] OPCAO DE APRENDIZAGEM; [pt] ALGORITMOS GENETICOS; [en] GENETIC ALGORITHMS; [pt] FATOR DE CHANCE; [en] CHANCE FACTOR

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

CALVETTE, L. D. M. D. (2015). [en] GENETIC ALGORITHMS AND REAL OPTIONS ON THE WILDCAT DRILLING OPTIMAL CHOICE. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24204

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

CALVETTE, LUIGI DE MAGALHAES DETOMI. “[en] GENETIC ALGORITHMS AND REAL OPTIONS ON THE WILDCAT DRILLING OPTIMAL CHOICE.” 2015. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24204.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

CALVETTE, LUIGI DE MAGALHAES DETOMI. “[en] GENETIC ALGORITHMS AND REAL OPTIONS ON THE WILDCAT DRILLING OPTIMAL CHOICE.” 2015. Web. 20 Jan 2021.

Vancouver:

CALVETTE LDMD. [en] GENETIC ALGORITHMS AND REAL OPTIONS ON THE WILDCAT DRILLING OPTIMAL CHOICE. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2015. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24204.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

CALVETTE LDMD. [en] GENETIC ALGORITHMS AND REAL OPTIONS ON THE WILDCAT DRILLING OPTIMAL CHOICE. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2015. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24204

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Ryerson University

5. Hajipour, Yassin. Non-periodic inspection of optimization of repairable systems.

Degree: 2016, Ryerson University

URL: https://digital.library.ryerson.ca/islandora/object/RULA%3A5215

► This study proposes models to find the optimal non-periodic inspection interval over a finite planning horizon for two types of multi-component repairable systems. The first… (more)

▼ This study proposes models to find the optimal non-periodic inspection interval over a finite planning horizon for two types of multi-component repairable systems. The first system consists of hard-type and soft-type components, and the second system is a k-out-of-m system with m identical components. The failures of components in both systems follow a non-homogeneous Poisson process. The failure of soft-type components and the failure of components in a k-out-of-m system when the number of failed components is still less than m-k+1, are soft failures. Soft failures are revealed only at scheduled inspections or when an event of opportunistic inspection or a system failure occurs. The failures of hard-type components or the failure of (m-k+1)th failed component in a k-out-of-m system are hard failures, and cause the system to stop functioning. Hard failures are revealed immediately and the failed components are fixed. In this study, a failed component is either replaced or minimally repaired according to its age at failure time. To find the optimal inspection schedules for the systems, we minimize the total expected cost of the systems over a finite planning horizon. The total cost for the first type of system includes the costs of components’ minimal repairs, replacements, downtimes, and the scheduled inspections. The total cost of a k-out-of-m system has an additional penalty cost for system failures. We consider a binary variable for a possible scheduled inspection’s time, in which 1 indicates performing a planned inspection at that time, and 0 shows no inspection to be performed. Thus, our goal is to find the optimal vector of binary decision variables which results in the minimum total cost of the system. A recursive formula is developed to calculate the expected number of minimal repairs, replacements and downtime of soft-type components. However since obtaining the expected values from the mathematical formula is cumbersome, we develop a simulation model to obtain the total expected cost for a given non-periodic inspection scheme. We then integrate the simulation model with a genetic algorithm to obtain the optimal inspection scheme.

Subjects/Keywords: Inspections; Genetic algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Hajipour, Y. (2016). Non-periodic inspection of optimization of repairable systems. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A5215

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hajipour, Yassin. “Non-periodic inspection of optimization of repairable systems.” 2016. Thesis, Ryerson University. Accessed January 20, 2021. https://digital.library.ryerson.ca/islandora/object/RULA%3A5215.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hajipour, Yassin. “Non-periodic inspection of optimization of repairable systems.” 2016. Web. 20 Jan 2021.

Vancouver:

Hajipour Y. Non-periodic inspection of optimization of repairable systems. [Internet] [Thesis]. Ryerson University; 2016. [cited 2021 Jan 20]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A5215.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hajipour Y. Non-periodic inspection of optimization of repairable systems. [Thesis]. Ryerson University; 2016. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A5215

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

6. RAPHAEL ARAUJO SAMPAIO. [en] A STUDY ON ELLIPSOIDAL CLUSTERING.

Degree: 2019, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=36126

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[pt] A análise de agrupamento não supervisionado, o processo que consistem em agrupar conjuntos de pontos de acordo com um ou mais critérios de similaridade,… (more)

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[pt] A análise de agrupamento não supervisionado, o processo que consistem em agrupar conjuntos de pontos de acordo com um ou mais critérios de similaridade, tem desempenhado um papel essencial em vários campos. O dois algoritmos mais populares para esse processão são o k-means e o Gaussian Mixture Models (GMM). O primeiro atribui cada ponto a um único cluster e usa a distância Euclidiana como similaridade. O último determina uma matriz de probabilidade de pontos pertencentes a clusters, e usa distância de Mahalanobis como similaridade. Além da diferença no método de atribuição - a chamada atribuição hard para o primeiro e a atribuição soft para o último - os algoritmos também diferem em relação à estrutura do cluster, ou forma: o k-means considera estruturas esféricas no dados; enquanto o GMM considera elipsoidais através da estimação de matrizes de covariância. Neste trabalho, um problema de otimização matemática que combina a atribuição hard com a estrutura do cluster elipsoidal é detalhado e formulado. Uma vez que a estimativa da covariância desempenha um papel importante no comportamento de estruturas agrupamentos elipsoidais, técnicas de regularizações são exploradas. Neste contexto, dois métodos de meta-heurística, uma perturbação Random Swap e um algoritmo híbrido genético, são adaptados, e seu impacto na melhoria do desempenho dos métodos é estudado. O objetivo central dividido em três: compreender as condições em que as estruturas de agrupamento elipsoidais são mais benéficas que as esféricas; determinar o impacto da estimativa de covariância com os métodos de regularização; e analisar o efeito das meta-heurísticas de otimização global na análise de agrupamento não supervisionado. Finalmente, a fim de fornecer bases para a comparação das presentes descobertas com futuros trabalhos relacionados, foi gerada uma base de dados com um extenso benchmark contendo análise das variações de diferentes tamanhos, formas, número de grupos e separabilidade, e seu impacto nos resultados de diferentes algoritmos de agrupamento. Além disso, pacotes escritos na linguagem Julia foram disponibilizados com os algoritmos estudados ao longo deste trabalho.

[en] Unsupervised cluster analysis, the process of grouping sets of points according to one or more similarity criteria, plays an essential role in various fields. The two most popular algorithms for this process are the k-means and the Gaussian Mixture Models (GMM). The former assigns each point to a single cluster and uses Euclidean distance as similarity. The latter determines a probability matrix of points to belong to clusters, and the Mahalanobis distance is the underlying similarity. Apart from the difference in the assignment method - the so-called hard assignment for the former and soft assignment for the latter - the algorithms also differ concerning the cluster structure, or shape: the k-means considers spherical structures in the data; while the GMM considers ellipsoidal ones through the estimation of covariance matrices. In this work, a mathematical optimization…

Advisors/Committee Members: MARCUS VINICIUS SOLEDADE POGGI DE ARAGAO.

Subjects/Keywords: [pt] ALGORITMOS GENETICOS; [en] GENETIC ALGORITHMS; [pt] REGULARIZACAO; [en] REGULARIZATION; [pt] RECONHECIMENTO DE PADRAO; [en] PATTERN RECOGNITION; [pt] AGRUPAMENTOS ELIPSOIDAIS; [en] ELLIPSOIDAL CLUSTERING; [pt] RANDOM SWAP; [en] RANDOM SWAP

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

SAMPAIO, R. A. (2019). [en] A STUDY ON ELLIPSOIDAL CLUSTERING. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=36126

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

SAMPAIO, RAPHAEL ARAUJO. “[en] A STUDY ON ELLIPSOIDAL CLUSTERING.” 2019. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=36126.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

SAMPAIO, RAPHAEL ARAUJO. “[en] A STUDY ON ELLIPSOIDAL CLUSTERING.” 2019. Web. 20 Jan 2021.

Vancouver:

SAMPAIO RA. [en] A STUDY ON ELLIPSOIDAL CLUSTERING. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2019. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=36126.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SAMPAIO RA. [en] A STUDY ON ELLIPSOIDAL CLUSTERING. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2019. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=36126

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

7. [No author]. [pt] INVESTIGANDO REGIMES ÓTIMOS PARA PREVISÃO NO MERCADO DE AÇÕES.

Degree: 2020, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47988

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[pt] A previsão de movimentos futuros para o mercado de ações é conhecidamente uma tarefa difícil de ser satisfatoriamente realizada. Além disso, a própria possibilidade… (more)

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[pt] A previsão de movimentos futuros para o mercado de ações é conhecidamente uma tarefa difícil de ser satisfatoriamente realizada. Além disso, a própria possibilidade desta previsão é constantemente questionada na literatura. O estudo presente investiga se essa dificuldade poderia ser amenizada escolhendo janelas específicas de tempo, onde uma dinâmica mais evidente prevaleça, e se a identificação desses períodos pode ser aprendida através de dados passados. Um framework é proposto para tratar desses problemas. Esse framework é nomeado de Predictability Crawler (P-Craw). A proposta usa rotinas de otimização como o Particle Swarm Optimization (PSO) e Algorítimos Genéticos (GA) para selecionar sub-conjuntos de dados históricos onde modelos de aprendizado estatístico possam ser treinados de forma mais eficiente. Para validar a acurácia do método, este é testado em dois diferentes conjuntos de dados. Primeiro, simulações com diferentes níveis de ruído são geradas. Nelas, o P-Craw é capaz de identificar os subconjuntos ótimos em cenários com 20 por cento a 100 por cento de amostras previsíveis. Por fim, dados de transações intradiárias da bolsa de valores brasileira (BOVESPA) são agregados e processados uma matrix de variáveis de entrada e um vetor de previsões. Quando o P-Craw é testado contra o método usual de treinar os modelos em todo conjunto histórico disponível nos dados da BOVESPA, o framework é capaz de aumentar significativamente o número de vezes que o modelo acerta a direção do movimento do preço das ações, enquanto consegue chegar a reduzir em até 19 por cento o erro médio absoluto da tarefa.

[en] Predicting stock movements in the market its known to be an extremely difficult task. More than that, the predictability of the series itself is a controversial matter. The present study investigates if this difficulty could be alleviated by choosing specific windows of time where a more structured dynamic prevails, and whether the identification of those moments could be learned from past data. In order to do that, a novel framework is proposed. This framework is called the Predictability Crawler (P-Craw). It uses optimizations routines such as the Particle Swarm Optimization (PSO) or Genetic Algorithms (GA) to select subsets of historical data where statistical learning algorithms can be more efficiently trained. To access the accuracy of the method, it is tested against two different datasets. First, simulated data with varying percentage of noise is generated and used. In the simulations, The P-Craw is able to reliably identify the optimal subsets in scenarios ranging from 20 percent to 100 percent of predictable samples in the data. Second, intraday data from the Brazilian stocks exchange (BOVESPA) is collected and aggregated into feature and target matrices. When benchmarked against training with the whole samples in the BOVESPA data, the framework is able to significantly raise the correct directional changes of the trained models while reducing the Mean Absolute Error in up to 19 percent.

Advisors/Committee Members: MARLEY MARIA BERNARDES REBUZZI VELLASCO.

Subjects/Keywords: [pt] SERIES TEMPORAIS; [en] TIME SERIES; [pt] MERCADO DE ACOES; [en] ACTIONS MARKET; [pt] PREVISIBILIDADE; [en] PREVISIBILITY; [pt] PSO; [en] PSO; [pt] ALGORITIMOS GENETICOS; [en] GENETIC ALGORITHMS

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

author], [. (2020). [pt] INVESTIGANDO REGIMES ÓTIMOS PARA PREVISÃO NO MERCADO DE AÇÕES. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47988

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

author], [No. “[pt] INVESTIGANDO REGIMES ÓTIMOS PARA PREVISÃO NO MERCADO DE AÇÕES.” 2020. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47988.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

author], [No. “[pt] INVESTIGANDO REGIMES ÓTIMOS PARA PREVISÃO NO MERCADO DE AÇÕES.” 2020. Web. 20 Jan 2021.

Vancouver:

author] [. [pt] INVESTIGANDO REGIMES ÓTIMOS PARA PREVISÃO NO MERCADO DE AÇÕES. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2020. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47988.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

author] [. [pt] INVESTIGANDO REGIMES ÓTIMOS PARA PREVISÃO NO MERCADO DE AÇÕES. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2020. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=47988

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

8. IURY STEINER DE OLIVEIRA BEZERRA. [en] INVESTIGATION OF AN AB INITIO MODEL TO ELECTRONIC STRUCTURE OF ATOMS BASED ON EVOLUTIVE ALGORITMS, WAVELETS AND LAGUERRE POLYNOMIALS.

Degree: 2018, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34924

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[pt] A simulação da estrutura eletrônica de átomos e moléculas, desde do início da década de 90, tem se mostrado uma ferramenta imprescindível para o… (more)

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[pt] A simulação da estrutura eletrônica de átomos e moléculas, desde do início da década de 90, tem se mostrado uma ferramenta imprescindível para o desenvolvimento de áreas estratégicas, ainda emergentes, mas fundamentais, como por exemplo, a área de Nanotecnologia. No entanto, esse tipo de simulação, ainda hoje é de grande complexidade e exige alto poder computacional. Dessa forma, torna-se fundamental a criação de métodos de simulação mais precisos e computacionalmente menos custosos. Este trabalho utiliza Algoritmos Evolutivos e métodos de Inteligência Computacional junto de algumas ferramentas desenvolvidas e estudadas tradicionalmente pela Matemática Aplicada em cálculos de estrutura eletrônica. Em particular, são construídas novas formas de aproximação de soluções para equação de Schrodinger, que contemplem os requisitos físicos necessários. Essas soluções serão nomeadas de funções de ondas evolucionárias, que neste trabalho serão tratadas como pontos em um espaço de Hilbert formado pelo fecho em L (2) da interseção das funções definidas na semi-reta, contínuas e de derivadas contínuas, simétricas ou antissimétricas com relação à permutação de suas coordenadas. São demonstrados alguns resultados, requisitos para utilização de Algoritmos Evolucionários e Séries de Fourier Generalizadas, baseadas em polinômios de Laguerre modificados e Wavelets. Esta pesquisa é desenvolvida inicialmente para sistemas de dois elétrons, e mais tarde é estendida para sistemas mais complexos, a fim de criar uma abordagem alternativa as tradicionais.

[en] The simulation of the electronic structure of atoms and molecules has been shown to be, from the beginning of 90 s, an indispensable tool for the development of strategic areas, that are still emergent, but fundamental, like nanotechnology. However, this type of simulation is still of great complexity today and demands high computational power. Thus, the creation of more precise and less costly methods becomes fundamental. With the elaboration of this research, the intention is to create alternatives basis that can be used into the traditional methods of simulation of electronic structure, such as the Hartree-Fock method, GVB, among others. This essay intends to investigate part of the mathematical tools used in the calculations of electronic structure, in order to create disruptive approaches, related to the precision or velocity of the obtainment of relevant results. The new methods are based in Computational Intelligence and concepts of Functional Analysis like Wavelets.

Advisors/Committee Members: MARCO AURÉLIO CAVALCANTI PACHECO.

Subjects/Keywords: [pt] ALGORITMOS EVOLUCIONARIOS; [en] EVOLUTIONARY ALGORITHMS; [pt] NANOTECNOLOGIA; [en] NANOTECHNOLOGY; [pt] MECANICA QUANTICA; [en] QUANTUM MECHANICS; [pt] QUIMICA COMPUTACIONAL; [en] COMPUTATIONAL CHEMISTRY; [pt] ONDELETAS; [en] WAVELETS; [pt] ALGORITMOS GENETICOS; [en] GENETIC ALGORITHMS; [pt] QUIMICA QUANTICA; [en] QUANTUM CHEMISTRY

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

BEZERRA, I. S. D. O. (2018). [en] INVESTIGATION OF AN AB INITIO MODEL TO ELECTRONIC STRUCTURE OF ATOMS BASED ON EVOLUTIVE ALGORITMS, WAVELETS AND LAGUERRE POLYNOMIALS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34924

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

BEZERRA, IURY STEINER DE OLIVEIRA. “[en] INVESTIGATION OF AN AB INITIO MODEL TO ELECTRONIC STRUCTURE OF ATOMS BASED ON EVOLUTIVE ALGORITMS, WAVELETS AND LAGUERRE POLYNOMIALS.” 2018. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34924.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

BEZERRA, IURY STEINER DE OLIVEIRA. “[en] INVESTIGATION OF AN AB INITIO MODEL TO ELECTRONIC STRUCTURE OF ATOMS BASED ON EVOLUTIVE ALGORITMS, WAVELETS AND LAGUERRE POLYNOMIALS.” 2018. Web. 20 Jan 2021.

Vancouver:

BEZERRA ISDO. [en] INVESTIGATION OF AN AB INITIO MODEL TO ELECTRONIC STRUCTURE OF ATOMS BASED ON EVOLUTIVE ALGORITMS, WAVELETS AND LAGUERRE POLYNOMIALS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34924.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

BEZERRA ISDO. [en] INVESTIGATION OF AN AB INITIO MODEL TO ELECTRONIC STRUCTURE OF ATOMS BASED ON EVOLUTIVE ALGORITMS, WAVELETS AND LAGUERRE POLYNOMIALS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34924

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

9. JOHNNY ALEXANDER BASTIDAS OTERO. [en] GENETIC ALGORITHMS APPLIED TO THE SOLUTION OF THE BIOMAGNETIC INVERSE PROBLEM.

Degree: 2016, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28372

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[pt] Sinais bioelétricos fornecem informações importantes sobre a função fisiológica de muitos organismos vivos. Em magnetismo, denomina-se problema direto aquele em que se determina o… (more)

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[pt] Sinais bioelétricos fornecem informações importantes sobre a função fisiológica de muitos organismos vivos. Em magnetismo, denomina-se problema direto aquele em que se determina o campo magnético a partir do conhecimento da fonte de corrente que o gerou. Por outro lado, existem situações em que se deseja determinar a fonte de corrente a partir de valores de campo magnético medidos. Esse tipo de problema é usual em Biomagnetismo e é denominado problema inverso. Por exemplo, com base em medições do campo magnético cardíaco é possível inferir sobre a atividade elétrica, no tecido cardíaco, que foi responsável por sua geração. Este trabalho propõe, apresenta e discute uma nova técnica destinada a resolver o problema biomagnético inverso, por meio de algoritmos genéticos. Objetiva-se estimar a posição, a orientação e a magnitude dos dipolos de corrente equivalentes, responsáveis pela geração de mapas de campos biomagnéticos obtidos experimentalmente por meio de medições realizadas em corações isolados de coelho utilizando um sistema SQUID de 16 canais. O algoritmo busca identificar a distribuição de dipolos que melhor se ajusta aos dados experimentais, objetivando minimizar o erro entre o mapa de campo magnético medido e o obtido por meio das soluções estimadas. O conhecimento dos parâmetros dos dipolos de corrente, em diferentes instantes de tempo, permite a correta interpretação e análise da informação médica obtida a partir dos campos biomagnéticos medidos experimentalmente, auxiliando na definição de diagnósticos e orientação de abordagens terapêuticas.

[en] Bioelectric signals provide important information about the physiological function of many living organisms. In magnetism, the so-called direct problem deals with the determination of the magnetic field associated to well known current sources. On the other hand, there are situations where it is necessary to determine the current source responsible for the generation of a measured magnetic field. This type of problem is common in Biomagnetism and is called inverse problem. For example, based on cardiac magnetic field measurements it is possible to infer the electrical activity in the heart tissue, responsible for its generation. This work proposes, presents and discusses a new technique designed to solve the biomagnetic inverse problem by genetic algorithms. It is intended to estimate the position, orientation and magnitude of the equivalent current dipoles, responsible for the generation of biomagnetic field maps measured with a 16 channel SQUID system. The algorithm attempts to identify the distribution of dipoles that best fits the measured experimental data, aiming at minimizing the error between the experimental magnetic field maps and those obtained by the estimated solutions. The experimental data analyzed in this study were acquired by measurements in isolated rabbit hearts. The knowledge of parameters of current dipoles at different instants of time allows the correct interpretation and analysis of medical information obtained from the…

Advisors/Committee Members: EDUARDO COSTA DA SILVA, EDUARDO COSTA DA SILVA, EDUARDO COSTA DA SILVA.

Subjects/Keywords: [pt] BIOMAGNETISMO; [en] BIOMAGNETISM; [pt] ALGORITMOS GENETICOS; [en] GENETIC ALGORITHMS; [pt] DIPOLO ELETRICO; [pt] PROBLEMA INVERSO BIOMAGNETICO; [en] BIOMAGNETIC INVERSE PROBLEM; [pt] MAGNETOCARDIOGRAFIA; [en] MAGNETOCARDIOGRAPHY

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

OTERO, J. A. B. (2016). [en] GENETIC ALGORITHMS APPLIED TO THE SOLUTION OF THE BIOMAGNETIC INVERSE PROBLEM. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28372

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

OTERO, JOHNNY ALEXANDER BASTIDAS. “[en] GENETIC ALGORITHMS APPLIED TO THE SOLUTION OF THE BIOMAGNETIC INVERSE PROBLEM.” 2016. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28372.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

OTERO, JOHNNY ALEXANDER BASTIDAS. “[en] GENETIC ALGORITHMS APPLIED TO THE SOLUTION OF THE BIOMAGNETIC INVERSE PROBLEM.” 2016. Web. 20 Jan 2021.

Vancouver:

OTERO JAB. [en] GENETIC ALGORITHMS APPLIED TO THE SOLUTION OF THE BIOMAGNETIC INVERSE PROBLEM. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2016. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28372.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

OTERO JAB. [en] GENETIC ALGORITHMS APPLIED TO THE SOLUTION OF THE BIOMAGNETIC INVERSE PROBLEM. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2016. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28372

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

10. ROBERTO CARLOS PEJENDINO JOJOA. [en] OPTIMIZATION OF CONTACT GRIDS FOR SOLAR CELLS WITH GENETIC ALGORITHMS.

Degree: 2018, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34922

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[pt] Altas resistências elétricas em série e baixas resistências em paralelo são fontes de perdas em dispositivos Fotovoltaicos (PV). Em dispositivos que operam sob concentração,… (more)

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[pt] Altas resistências elétricas em série e baixas resistências em paralelo são fontes de perdas em dispositivos Fotovoltaicos (PV). Em dispositivos que operam sob concentração, esses costumam ser os principais fatores limitantes para o aumento da eficiência de conversão. Excluindo fatores externos associados a falhas no processo de produção, a resistência elétrica em série depende de fatores intrínsecos aos materiais e à estrutura de camadas do dispositivo fotovoltaico. Dessa forma, para minimizar o seu valor é extremamente importante planejar adequadamente esses parâmetros construtivos antes da produção dos dispositivos. Um dos fatores mais impactantes na resistência em série é o desenho da malha de dedos coletores do contato elétrico frontal. Por outro lado, minimizar a resistência em série do contato elétrico requer o aumento da área metálica da superfície frontal, que serve de janela para a radiação solar. Portanto, deve haver um compromisso na redução das perdas elétricas e ópticas. Nesse trabalho, apresentamos os resultados da otimização do desenho da malha de dedos coletores para o contato elétrico frontal para três diferentes geometrias obtidas por algoritmos genéticos. As geometrias escolhidas foram a retangular, tradicional para a produção desse tipo de dispositivo, a hexagonal e a diamante. Além disso, comparamos os resultados obtidos com os de um dispositivo produzido com uma malha otimizada por um método de cálculo analítico. Ao final, discutimos as melhorias introduzidas pelas novas geometrias e apresentamos a configuração otimizada, que foi obtido para uma célula solar de tamanho 5x5 mm com uma estrutura retangular de fingers, com uma redução de perdas de 54,42 por cento que leva a um aumento aproximado de 1,40 por cento em eficiência.

[en] High electrical resistances in series and low resistances in parallel are sources of losses in Photovoltaic (PV) devices. In devices that operate under concentration, these are often the main limiting factors for increasing conversion efficiency. Excluding external factors associated with failures in the production process, the series electrical resistance depends on factors intrinsic to the materials and the layer structure of the photovoltaic device. Thus, to minimize their value it is extremely important to properly plan these constructive parameters prior to the production of the devices. One of the most striking factors in the series resistance is the design of the mesh of collecting fingers of the frontal electrical contact. On the other hand, minimizing the series resistance of the electrical contact requires the increase of the metallic area of the frontal surface, which serves as a window for solar radiation. Therefore, there must be a commitment to reduce electrical and optical losses. In this work, we present the results of the optimization of the design of the mesh of collecting fingers for the frontal electrical contact for three different geometries obtained by genetic algorithms. The geometries chosen were the rectangular, traditional for the…

Advisors/Committee Members: PATRICIA LUSTOZA DE SOUZA.

Subjects/Keywords: [pt] CELULA FOTOVOLTAICA; [en] PHOTOVOLTAIC CELL; [pt] ALGORITMOS GENETICOS; [en] GENETIC ALGORITHMS; [pt] OTIMIZACAO DE REDES DE CONTATO; [en] CONTACT GRIDS OPTIMIZATION; [pt] DEDOS COLETORES; [en] FINGERS COLLECTORS

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

JOJOA, R. C. P. (2018). [en] OPTIMIZATION OF CONTACT GRIDS FOR SOLAR CELLS WITH GENETIC ALGORITHMS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34922

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

JOJOA, ROBERTO CARLOS PEJENDINO. “[en] OPTIMIZATION OF CONTACT GRIDS FOR SOLAR CELLS WITH GENETIC ALGORITHMS.” 2018. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34922.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

JOJOA, ROBERTO CARLOS PEJENDINO. “[en] OPTIMIZATION OF CONTACT GRIDS FOR SOLAR CELLS WITH GENETIC ALGORITHMS.” 2018. Web. 20 Jan 2021.

Vancouver:

JOJOA RCP. [en] OPTIMIZATION OF CONTACT GRIDS FOR SOLAR CELLS WITH GENETIC ALGORITHMS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34922.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

JOJOA RCP. [en] OPTIMIZATION OF CONTACT GRIDS FOR SOLAR CELLS WITH GENETIC ALGORITHMS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34922

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

11. RAFAEL LIMA DE OLIVEIRA. [en] HISTORY MATCHING IN RESERVOIR SIMULATION MODELS BY COEVOLUTIONARY GENETIC ALGORITHMS AND MULTIPLE-POINT GEOESTATISTICS.

Degree: 2018, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35313

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[pt] Na área de Exploração e Produção (EeP) de petróleo, uma das tarefas mais importantes é o estudo minucioso das características do reservatório para a… (more)

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[pt] Na área de Exploração e Produção (EeP) de petróleo, uma das tarefas mais importantes é o estudo minucioso das características do reservatório para a criação de modelos de simulação que representem adequadamente as suas características. Durante a vida produtiva de um reservatório, o seu modelo de simulação correspondente precisa ser ajustado periodicamente, pois a disponibilidade de um modelo adequado é fundamental para a obtenção de previsões acertadas acerca da produção, e isto impacta diretamente a tomada de decisões gerenciais. O ajuste das propriedades do modelo se traduz em um problema de otimização complexo, onde a quantidade de variáveis envolvidas cresce com o aumento do número de blocos que compõem a malha do modelo de simulação, exigindo muito esforço por parte do especialista. A disponibilidade de uma ferramenta computacional, que possa auxiliar o especialista em parte deste processo, pode ser de grande utilidade tanto para a obtenção de respostas mais rápidas, quanto para a tomada de decisões mais acertadas. Diante disto, este trabalho combina inteligência computacional através de Algoritmo Genético Co-Evolutivo com Geoestatística de Múltiplos Pontos, propondo e implementando uma arquitetura de otimização aplicada ao ajuste de propriedades de modelos de reservatórios. Esta arquitetura diferencia-se das tradicionais abordagens por ser capaz de otimizar, simultaneamente, mais de uma propriedade do modelo de simulação de reservatório. Utilizou-se também, processamento distribuído para explorar o poder computacional paralelo dos algoritmos genéticos. A arquitetura mostrou-se capaz de gerar modelos que ajustam adequadamente as curvas de produção, preservando a consistência e a continuidade geológica do reservatório obtendo, respectivamente, 98 por cento e 97 por cento de redução no erro de ajuste aos dados históricos e de previsão. Para os mapas de porosidade e de permeabilidade, as reduções nos erros foram de 79 por cento e 84 por cento, respectivamente.

[en] In the Exploration and Production (EeP) of oil, one of the most important tasks is the detailed study of the characteristics of the reservoir for the creation of simulation models that adequately represent their characteristics. During the productive life of a reservoir, its corresponding simulation model needs to be adjusted periodically because the availability of an appropriate model is crucial to obtain accurate predictions about the production, and this directly impacts the management decisions. The adjustment of the properties of the model is translated into a complex optimization problem, where the number of variables involved increases with the increase of the number of blocks that make up the mesh of the simulation model, requiring too much effort on the part of a specialist. The availability of a computational tool that can assist the specialist on part of this process can be very useful both for obtaining quicker responses, as for making better decisions. Thus, this work combines computational intelligence through Coevolutionary…

Advisors/Committee Members: MARCO AURÉLIO CAVALCANTI PACHECO.

Subjects/Keywords: [pt] AJUSTE DE HISTORICO; [en] HISTORY MATCHING; [pt] ALGORITMOS GENETICOS CO-EVOLUTIVOS; [en] COEVOLUTIONARY GENETIC ALGORITHMS; [pt] GEOESTATISTICA DE MULTIPLOS PONTOS; [en] MULTIPLE-POINT GEOSTATISTICS

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

OLIVEIRA, R. L. D. (2018). [en] HISTORY MATCHING IN RESERVOIR SIMULATION MODELS BY COEVOLUTIONARY GENETIC ALGORITHMS AND MULTIPLE-POINT GEOESTATISTICS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

OLIVEIRA, RAFAEL LIMA DE. “[en] HISTORY MATCHING IN RESERVOIR SIMULATION MODELS BY COEVOLUTIONARY GENETIC ALGORITHMS AND MULTIPLE-POINT GEOESTATISTICS.” 2018. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

OLIVEIRA, RAFAEL LIMA DE. “[en] HISTORY MATCHING IN RESERVOIR SIMULATION MODELS BY COEVOLUTIONARY GENETIC ALGORITHMS AND MULTIPLE-POINT GEOESTATISTICS.” 2018. Web. 20 Jan 2021.

Vancouver:

OLIVEIRA RLD. [en] HISTORY MATCHING IN RESERVOIR SIMULATION MODELS BY COEVOLUTIONARY GENETIC ALGORITHMS AND MULTIPLE-POINT GEOESTATISTICS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

OLIVEIRA RLD. [en] HISTORY MATCHING IN RESERVOIR SIMULATION MODELS BY COEVOLUTIONARY GENETIC ALGORITHMS AND MULTIPLE-POINT GEOESTATISTICS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

12. WALLACE JOSE DAMASCENO DO NASCIMENTO. [en] THERMAL POWER PORTFOLIO VALUATION UNDER UNCERTAINTY: A HYBRID METHODOLOGY USING FUZZY NUMBERS, REAL OPTIONS AND OPTIMIZATION BY GENETIC ALGORITHMS.

Degree: 2017, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30498

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[pt] Os grandes agentes do mercado de energia dedicam muitos esforços na avaliação e decisão da alocação ótima de capital para a implementação de projetos,… (more)

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[pt] Os grandes agentes do mercado de energia dedicam muitos esforços na avaliação e decisão da alocação ótima de capital para a implementação de projetos, em decorrência do grande número de projetos candidatos em seus portfólios de investimentos. Essas decisões visam escolher o subconjunto de projetos a ser implementado, pois os recursos orçamentários são geralmente menores que o necessário para a implementação de todos eles. Muitos são os riscos apresentados, e quanto mais riscos e incertezas, maiores se tornam as dificuldades de avaliação e decisões de investimento de maneira otimizada. As metodologias clássicas para avaliação de portfólios de projetos de investimento são baseadas em maximizar os retornos (VPL, TIR, etc) e minimizar o risco (desvio-padrão do VPL, variância, etc). Muitas vezes, estes métodos tradicionais de avaliação podem não conseguir tratar adequadamente as flexibilidades gerenciais (Opções Reais) características dos projetos, assim como os riscos e incertezas, devido às possíveis dificuldades de solução e modelagem matemática (multi-variáveis) dos problemas. O desenvolvimento e aplicação de modelos alternativos, tais como os baseados na Teoria de Opções Reais, inclusive com a utilização de métodos de Inteligência Computacional, podem se mostrar mais adequados para estes problemas. Nesta tese é desenvolvida uma metodologia híbrida, apresentando um modelo de Opções Reais Fuzzy para a avaliação de projetos de Revamp por um agente do mercado de Geração Termelétrica de Energia, a partir de um Portfólio de Opções Reais em ambiente de incertezas. Para a seleção do subconjunto de projetos por faixa orçamentária, é aplicado um Algoritmo Genético para otimização multi-critério, através da utilização de um índice de ponderação retorno x risco (lâmbda).

[en] Large players in energy market dedicate many efforts in valuation and optimal capital allocation decision for their project implementation, due the large candidate projects number in their investment portfolios. These decisions aim to choose the projects subset to be implemented, because the monetary resources are generally smaller than necessary for all projects implementation. There are many risks, and with risks and uncertainties, greater become the difficulties in analysis and optimally investment decisions. The classical methods to investment portfolios are based on to maximize returns (NPV, IRR, among others) and to minimize risks (NPV standard deviation, variance, among others). Often, these traditional methods may not be able to handle properly the projects managerial flexibilities (Real Options), as well the risks and uncertainties, due to possible solution difficulties and mathematical modeling problems (multi variables). Alternative models development and implementation, such as those based on Real Options Theory, including the use of Computational Intelligence methods, may be more suitable for these problems. In this thesis, a hybrid methodology is developed, presenting a Fuzzy Real Options model for Revamp projects valuation by a…

Advisors/Committee Members: MARCO AURÉLIO CAVALCANTI PACHECO.

Subjects/Keywords: [pt] OPCOES REAIS; [en] REAL OPTIONS; [pt] INVESTIMENTO SOB INCERTEZA; [en] INVESTMENT UNDER UNCERTAUNTY; [pt] ALGORITMOS GENETICOS; [en] GENETIC ALGORITHMS; [pt] GERACAO TERMELETRICA; [pt] OTIMIZACAO DE PORTFOLIOS

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

NASCIMENTO, W. J. D. D. (2017). [en] THERMAL POWER PORTFOLIO VALUATION UNDER UNCERTAINTY: A HYBRID METHODOLOGY USING FUZZY NUMBERS, REAL OPTIONS AND OPTIMIZATION BY GENETIC ALGORITHMS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30498

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

NASCIMENTO, WALLACE JOSE DAMASCENO DO. “[en] THERMAL POWER PORTFOLIO VALUATION UNDER UNCERTAINTY: A HYBRID METHODOLOGY USING FUZZY NUMBERS, REAL OPTIONS AND OPTIMIZATION BY GENETIC ALGORITHMS.” 2017. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed January 20, 2021. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30498.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

NASCIMENTO, WALLACE JOSE DAMASCENO DO. “[en] THERMAL POWER PORTFOLIO VALUATION UNDER UNCERTAINTY: A HYBRID METHODOLOGY USING FUZZY NUMBERS, REAL OPTIONS AND OPTIMIZATION BY GENETIC ALGORITHMS.” 2017. Web. 20 Jan 2021.

Vancouver:

NASCIMENTO WJDD. [en] THERMAL POWER PORTFOLIO VALUATION UNDER UNCERTAINTY: A HYBRID METHODOLOGY USING FUZZY NUMBERS, REAL OPTIONS AND OPTIMIZATION BY GENETIC ALGORITHMS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2017. [cited 2021 Jan 20]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30498.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

NASCIMENTO WJDD. [en] THERMAL POWER PORTFOLIO VALUATION UNDER UNCERTAINTY: A HYBRID METHODOLOGY USING FUZZY NUMBERS, REAL OPTIONS AND OPTIMIZATION BY GENETIC ALGORITHMS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2017. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30498

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rochester Institute of Technology

13. Lamos-Sweeney, Joshua. Deep learning using genetic algorithms.

Degree: Computer Science (GCCIS), 2012, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/254

► Deep Learning networks are a new type of neural network that discovers important object features. These networks determine features without supervision, and are adept at… (more)

Subjects/Keywords: Deep learning; Genetic algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lamos-Sweeney, J. (2012). Deep learning using genetic algorithms. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/254

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lamos-Sweeney, Joshua. “Deep learning using genetic algorithms.” 2012. Thesis, Rochester Institute of Technology. Accessed January 20, 2021. https://scholarworks.rit.edu/theses/254.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lamos-Sweeney, Joshua. “Deep learning using genetic algorithms.” 2012. Web. 20 Jan 2021.

Vancouver:

Lamos-Sweeney J. Deep learning using genetic algorithms. [Internet] [Thesis]. Rochester Institute of Technology; 2012. [cited 2021 Jan 20]. Available from: https://scholarworks.rit.edu/theses/254.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lamos-Sweeney J. Deep learning using genetic algorithms. [Thesis]. Rochester Institute of Technology; 2012. Available from: https://scholarworks.rit.edu/theses/254

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Alberta

14. Shu, Lingyan. The impact of data structures on the performance of genetic-algorithm-based learning.

Degree: PhD, Department of Computing Science, 1992, University of Alberta

URL: https://era.library.ualberta.ca/files/bg257h66m

Subjects/Keywords: Genetic algorithms.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Shu, L. (1992). The impact of data structures on the performance of genetic-algorithm-based learning. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/bg257h66m

Chicago Manual of Style (16^th Edition):

Shu, Lingyan. “The impact of data structures on the performance of genetic-algorithm-based learning.” 1992. Doctoral Dissertation, University of Alberta. Accessed January 20, 2021. https://era.library.ualberta.ca/files/bg257h66m.

MLA Handbook (7^th Edition):

Shu, Lingyan. “The impact of data structures on the performance of genetic-algorithm-based learning.” 1992. Web. 20 Jan 2021.

Vancouver:

Shu L. The impact of data structures on the performance of genetic-algorithm-based learning. [Internet] [Doctoral dissertation]. University of Alberta; 1992. [cited 2021 Jan 20]. Available from: https://era.library.ualberta.ca/files/bg257h66m.

Council of Science Editors:

Shu L. The impact of data structures on the performance of genetic-algorithm-based learning. [Doctoral Dissertation]. University of Alberta; 1992. Available from: https://era.library.ualberta.ca/files/bg257h66m

Texas A&M University

15. Kumar, Akansha. An Iterative Optimization Method Using Genetic Algorithms and Gaussian Process Based Regression in Nuclear Reactor Design Applications.

Degree: PhD, Nuclear Engineering, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/159121

► The optimization of a complex system involves the determination of optimum values for a set of design parameters. The optimization search happens in order to… (more)

Subjects/Keywords: genetic algorithms; optimization; nuclear; reactor

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APA (6^th Edition):

Kumar, A. (2016). An Iterative Optimization Method Using Genetic Algorithms and Gaussian Process Based Regression in Nuclear Reactor Design Applications. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/159121

Chicago Manual of Style (16^th Edition):

Kumar, Akansha. “An Iterative Optimization Method Using Genetic Algorithms and Gaussian Process Based Regression in Nuclear Reactor Design Applications.” 2016. Doctoral Dissertation, Texas A&M University. Accessed January 20, 2021. http://hdl.handle.net/1969.1/159121.

MLA Handbook (7^th Edition):

Kumar, Akansha. “An Iterative Optimization Method Using Genetic Algorithms and Gaussian Process Based Regression in Nuclear Reactor Design Applications.” 2016. Web. 20 Jan 2021.

Vancouver:

Kumar A. An Iterative Optimization Method Using Genetic Algorithms and Gaussian Process Based Regression in Nuclear Reactor Design Applications. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1969.1/159121.

Council of Science Editors:

Kumar A. An Iterative Optimization Method Using Genetic Algorithms and Gaussian Process Based Regression in Nuclear Reactor Design Applications. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/159121

Texas A&M University

16. Gibbs, Trevor Howard. Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms.

Degree: MS, Petroleum Engineering, 2011, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399

► Horizontal well placement determination within a reservoir is a significant and difficult step in the reservoir development process. Determining the optimal well location is a… (more)

▼ Horizontal well placement determination within a reservoir is a significant and difficult step in the reservoir development process. Determining the optimal well location is a complex problem involving many factors including geological considerations, reservoir and fluid properties, economic costs, lateral direction, and technical ability. The most thorough approach to this problem is that of an exhaustive search, in which a simulation is run for every conceivable well position in the reservoir. Although thorough and accurate, this approach is typically not used in real world applications due to the time constraints from the excessive number of simulations. This project suggests the use of a genetic algorithm applied to the horizontal well placement problem in a gas reservoir to reduce the required number of simulations. This research aims to first determine if well placement optimization is even necessary in a gas reservoir, and if so, to determine the benefit of optimization. Performance of the genetic algorithm was analyzed through five different case scenarios, one involving a vertical well and four involving horizontal wells. The genetic algorithm approach is used to evaluate the effect of well placement in heterogeneous and anisotropic reservoirs on reservoir recovery. The wells are constrained by surface gas rate and bottom-hole pressure for each case. This project's main new contribution is its application of using genetic algorithms to study the effect of well placement optimization in gas reservoirs. Two fundamental questions have been answered in this research. First, does well placement in a gas reservoir affect the reservoir performance? If so, what is an efficient method to find the optimal well location based on reservoir performance? The research provides evidence that well placement optimization is an important criterion during the reservoir development phase of a horizontal-well project in gas reservoirs, but it is less significant to vertical wells in a homogeneous reservoir. It is also shown that genetic algorithms are an extremely efficient and robust tool to find the optimal location. Advisors/Committee Members: Zhu, Ding (advisor), Nasrabadi, Hadi (advisor), Sun, Yuefeng (committee member), Ehlig-Economides, Christine (committee member).

Subjects/Keywords: genetic; algorithms; optimization; well placement

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APA (6^th Edition):

Gibbs, T. H. (2011). Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399

Chicago Manual of Style (16^th Edition):

Gibbs, Trevor Howard. “Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms.” 2011. Masters Thesis, Texas A&M University. Accessed January 20, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399.

MLA Handbook (7^th Edition):

Gibbs, Trevor Howard. “Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms.” 2011. Web. 20 Jan 2021.

Vancouver:

Gibbs TH. Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms. [Internet] [Masters thesis]. Texas A&M University; 2011. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399.

Council of Science Editors:

Gibbs TH. Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms. [Masters Thesis]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399

Nelson Mandela Metropolitan University

17. Buys, Stefan. Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition.

Degree: Faculty of Engineering, the Built Environment and Information Technology, 2012, Nelson Mandela Metropolitan University

URL: http://hdl.handle.net/10948/d1008356

► Object or part recognition is of major interest in industrial environments. Current methods implement expensive camera based solutions. There is a need for a cost… (more)

Subjects/Keywords: Genetic algorithms; Software architecture

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APA (6^th Edition):

Buys, S. (2012). Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition. (Thesis). Nelson Mandela Metropolitan University. Retrieved from http://hdl.handle.net/10948/d1008356

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Buys, Stefan. “Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition.” 2012. Thesis, Nelson Mandela Metropolitan University. Accessed January 20, 2021. http://hdl.handle.net/10948/d1008356.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Buys, Stefan. “Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition.” 2012. Web. 20 Jan 2021.

Vancouver:

Buys S. Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition. [Internet] [Thesis]. Nelson Mandela Metropolitan University; 2012. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/10948/d1008356.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Buys S. Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition. [Thesis]. Nelson Mandela Metropolitan University; 2012. Available from: http://hdl.handle.net/10948/d1008356

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Oregon State University

18. Dill, Karen M. Growing digital circuits : logic synthesis and minimization with genetic operators.

Degree: MS, Electrical and Computer Engineering, 1996, Oregon State University

URL: http://hdl.handle.net/1957/34241

► This research applies the biologically inspired, artificial evolutionary processes of Genetic Algorithms and Genetic Programming to digital hardware circuit synthesis and minimization. In this new… (more)

▼ This research applies the biologically inspired, artificial evolutionary processes of Genetic Algorithms and Genetic Programming to digital hardware circuit synthesis and minimization. In this new application, three approaches are taken to genetic hardware development. First, as a method for logic synthesis, Genetic Programming is applied to the building of logic functions. Experimental results have shown the logic equations from this technique produce better than 88% coverage of the given truth-tables, but the method cannot guarantee complete (100%) coverage. Secondly, to better achieve complete function coverage, an XOR Correction Circuit Algorithm used in conjunction with the Genetic Logic Synthesis was developed. With this algorithm, the genetic logic synthesis can reiteratively attempt coverage by formulating its own selective "correction" functions, for input combinations where complete truth table coverage has not previously been achieved. With this technique, complete function coverage was synthesized in all experiments conducted. The third application of the paradigm is to the minimization of Reed-Muller Equations. In this application, a Genetic Algorithm is implemented only in the search space of all "correct", functionally equivalent equations, with only the task of finding reductions. With this limited search space the solutions have absolute guaranteed function coverage, as well as a better defined focus for the genetic evolutionary process. In both the logic synthesis and minimization processes the genetic operators determine efficient circuit implementations and reductions. The results are often different from those of human designers. Because the genetic techniques incorporate logical testing into the design and build process, one can be assured that the circuit will function as derived on completion. For all three applications, the effects of a number of evolutionary parameters on the genetic operators' problem solving capability are examined. The resulting logic and logic minimizations are also compared with both arbitrarily defined functions and well known logic synthesis benchmarks. It has been shown that genetic operators applied to digital logic can effectively find good solutions for both logic synthesis and logic minimization. Advisors/Committee Members: Herzog, James H. (advisor).

Subjects/Keywords: Genetic algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Dill, K. M. (1996). Growing digital circuits : logic synthesis and minimization with genetic operators. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/34241

Chicago Manual of Style (16^th Edition):

Dill, Karen M. “Growing digital circuits : logic synthesis and minimization with genetic operators.” 1996. Masters Thesis, Oregon State University. Accessed January 20, 2021. http://hdl.handle.net/1957/34241.

MLA Handbook (7^th Edition):

Dill, Karen M. “Growing digital circuits : logic synthesis and minimization with genetic operators.” 1996. Web. 20 Jan 2021.

Vancouver:

Dill KM. Growing digital circuits : logic synthesis and minimization with genetic operators. [Internet] [Masters thesis]. Oregon State University; 1996. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1957/34241.

Council of Science Editors:

Dill KM. Growing digital circuits : logic synthesis and minimization with genetic operators. [Masters Thesis]. Oregon State University; 1996. Available from: http://hdl.handle.net/1957/34241

Oregon State University

19. Canpolat, Necati. Optimization of seasonal irrigation scheduling by genetic algorithms.

Degree: PhD, Bioresource Engineering, 1997, Oregon State University

URL: http://hdl.handle.net/1957/34323

► In this work, we first introduce a novel approach to the long term irrigation scheduling using Genetic Algorithms (GAs). We explore the effectiveness of GAs… (more)

▼ In this work, we first introduce a novel approach to the long term irrigation scheduling using Genetic Algorithms (GAs). We explore the effectiveness of GAs in the context of optimizing nonlinear crop models and describe application requirements and implementation of the technique. GAs were found to converge quickly to near-optimal solutions. Second, we analyze the relationship between GA control parameters (population size, crossover rate, and mutation rate) and performance. We identify a combination of population, mutation, and crossover which searched the fitness landscape efficiently. The results suggest that smaller populations are able to provide better performance at relatively low mutation rates. More stable outcomes were generated using low mutation rates. Without crossover the quality of solutions were generally impaired, and the search process was lengthened. Aside from crossover rate zero, no other crossover rates significantly differed. The behaviors observed for best, online, offline, and average performances were sensitive to the combined influences control parameters. Interaction among control parameters was strongly indicated. Finally, several adaptive penalty techniques are presented for handling constraints in GAs, and their effectiveness is demonstrated. The constant penalty function suffered from sensitivity to settings of penalty coefficients, and was not successful in satisfying constraints. The adaptive penalty functions utilizes violation distance based metrics and search time based scaling using generation or trials number, and fitness values to penalize infeasible solutions, as the distance from the feasible region or number of generations increases so does the penalty. They were quite successful in providing solutions with minimal effort. They adapt the penalty as the search continues, encouraging feasible solutions to emerge over the time. Adaptive approaches presented here are flexible, efficient, and robust to parameter settings. Advisors/Committee Members: Bolte, John P. (advisor), Moss, Dave (committee member).

Subjects/Keywords: Genetic algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Canpolat, N. (1997). Optimization of seasonal irrigation scheduling by genetic algorithms. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/34323

Chicago Manual of Style (16^th Edition):

Canpolat, Necati. “Optimization of seasonal irrigation scheduling by genetic algorithms.” 1997. Doctoral Dissertation, Oregon State University. Accessed January 20, 2021. http://hdl.handle.net/1957/34323.

MLA Handbook (7^th Edition):

Canpolat, Necati. “Optimization of seasonal irrigation scheduling by genetic algorithms.” 1997. Web. 20 Jan 2021.

Vancouver:

Canpolat N. Optimization of seasonal irrigation scheduling by genetic algorithms. [Internet] [Doctoral dissertation]. Oregon State University; 1997. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/1957/34323.

Council of Science Editors:

Canpolat N. Optimization of seasonal irrigation scheduling by genetic algorithms. [Doctoral Dissertation]. Oregon State University; 1997. Available from: http://hdl.handle.net/1957/34323

University of Guelph

20. Brown, Joseph Alexander. Regression and Classification from Extinction.

Degree: PhD, School of Computer Science, 2014, University of Guelph

URL: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793

► Evolutionary Algorithms use the principles of natural selection and biological evolution to act as search and optimization tools. Two novel Spatially Structured Evolutionary Algorithms: the… (more)

Subjects/Keywords: Genetic Algorithms; Bioinformatics; Evolutionary Computation

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APA (6^th Edition):

Brown, J. A. (2014). Regression and Classification from Extinction. (Doctoral Dissertation). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793

Chicago Manual of Style (16^th Edition):

Brown, Joseph Alexander. “Regression and Classification from Extinction.” 2014. Doctoral Dissertation, University of Guelph. Accessed January 20, 2021. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793.

MLA Handbook (7^th Edition):

Brown, Joseph Alexander. “Regression and Classification from Extinction.” 2014. Web. 20 Jan 2021.

Vancouver:

Brown JA. Regression and Classification from Extinction. [Internet] [Doctoral dissertation]. University of Guelph; 2014. [cited 2021 Jan 20]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793.

Council of Science Editors:

Brown JA. Regression and Classification from Extinction. [Doctoral Dissertation]. University of Guelph; 2014. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793

University of Adelaide

21. Sullivan, Nicholas David. Task Allocation and Collaborative Localisation in Multi-Robot Systems.

Degree: 2019, University of Adelaide

URL: http://hdl.handle.net/2440/120578

► To utilise multiple robots, it is fundamental to know what they should do, called task allocation, and to know where the robots are, called localisation.… (more)

▼ To utilise multiple robots, it is fundamental to know what they should do, called task allocation, and to know where the robots are, called localisation. The order that tasks are completed in is often important, and makes task allocation difficult to solve (40 tasks have 1047 different ways of completing them). Algorithms in literature range from fast methods that provide reasonable allocations, to slower methods that can provide optimal allocations. These algorithms work well for systems with identical robots, but do not utilise robot differences for superior allocations when robots are non-identical. They also can not be applied to robots that can use different tools, where they must consider which tools to use for each task. Robot localisation is performed using sensors which are often assumed to always be available. This is not the case in GPS-denied environments such as tunnels, or on long-range missions where replacement sensors are not readily available. A promising method to overcome this is collaborative localisation, where robots observe one another to improve their location estimates. There has been little research on what robot properties make collaborative localisation most effective, or how to tune systems to make it as accurate as possible. Most task allocation algorithms do not consider localisation as part of the allocation process. If task allocation algorithms limited inter-robot distance, collaborative localisation can be performed during task completion. Such an algorithm could equally be used to ensure robots are within communication distance, and to quickly detect when a robot fails. While some algorithms for this exist in literature, they provide a weak guarantee of inter-robot distance, which is undesirable when applied to real robots. The aim of this thesis is to improve upon task allocation algorithms by increasing task allocation speed and efficiency, and supporting robot tool changes. Collaborative localisation parameters are analysed, and a task allocation algorithm that enables collaborative localisation on real robots is developed. This thesis includes a compendium of journal articles written by the author. The four articles forming the main body of the thesis discuss the multi-robot task allocation and localisation research during the author’s candidature. Two appendices are included, representing conference articles written by the author that directly relate to the thesis. Advisors/Committee Members: Grainger, Steven (advisor), School of Mechanical Engineering (school).

Subjects/Keywords: multi-robot; genetic algorithms; localisation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sullivan, N. D. (2019). Task Allocation and Collaborative Localisation in Multi-Robot Systems. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/120578

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sullivan, Nicholas David. “Task Allocation and Collaborative Localisation in Multi-Robot Systems.” 2019. Thesis, University of Adelaide. Accessed January 20, 2021. http://hdl.handle.net/2440/120578.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sullivan, Nicholas David. “Task Allocation and Collaborative Localisation in Multi-Robot Systems.” 2019. Web. 20 Jan 2021.

Vancouver:

Sullivan ND. Task Allocation and Collaborative Localisation in Multi-Robot Systems. [Internet] [Thesis]. University of Adelaide; 2019. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/2440/120578.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sullivan ND. Task Allocation and Collaborative Localisation in Multi-Robot Systems. [Thesis]. University of Adelaide; 2019. Available from: http://hdl.handle.net/2440/120578

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chapman University

22. James, Kevin. Estimating Auction Equilibria using Individual Evolutionary Learning.

Degree: PhD, Computational and Data Sciences, 2019, Chapman University

URL: https://digitalcommons.chapman.edu/cads_dissertations/1

► I develop the Generalized Evolutionary Nash Equilibrium Estimator (GENEE) library. The tool is designed to provide a generic computational library for running genetic algorithms… (more)

Subjects/Keywords: genetic algorithms; Behavioral Economics

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APA (6^th Edition):

James, K. (2019). Estimating Auction Equilibria using Individual Evolutionary Learning. (Doctoral Dissertation). Chapman University. Retrieved from https://digitalcommons.chapman.edu/cads_dissertations/1

Chicago Manual of Style (16^th Edition):

James, Kevin. “Estimating Auction Equilibria using Individual Evolutionary Learning.” 2019. Doctoral Dissertation, Chapman University. Accessed January 20, 2021. https://digitalcommons.chapman.edu/cads_dissertations/1.

MLA Handbook (7^th Edition):

James, Kevin. “Estimating Auction Equilibria using Individual Evolutionary Learning.” 2019. Web. 20 Jan 2021.

Vancouver:

James K. Estimating Auction Equilibria using Individual Evolutionary Learning. [Internet] [Doctoral dissertation]. Chapman University; 2019. [cited 2021 Jan 20]. Available from: https://digitalcommons.chapman.edu/cads_dissertations/1.

Council of Science Editors:

James K. Estimating Auction Equilibria using Individual Evolutionary Learning. [Doctoral Dissertation]. Chapman University; 2019. Available from: https://digitalcommons.chapman.edu/cads_dissertations/1

Hong Kong University of Science and Technology

23. Law, Nga Lam. Parameter-free adaptive genetic algorithm.

Degree: 2007, Hong Kong University of Science and Technology

URL: http://repository.ust.hk/ir/Record/1783.1-5471 ; https://doi.org/10.14711/thesis-b987302 ; http://repository.ust.hk/ir/bitstream/1783.1-5471/1/th_redirect.html

► A new adaptive approach, which applies the concept of relative importance of information to the genetic algorithm, is developed. Selection, crossover and mutation are parameter-free… (more)

Subjects/Keywords: Genetic algorithms

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APA (6^th Edition):

Law, N. L. (2007). Parameter-free adaptive genetic algorithm. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-5471 ; https://doi.org/10.14711/thesis-b987302 ; http://repository.ust.hk/ir/bitstream/1783.1-5471/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Law, Nga Lam. “Parameter-free adaptive genetic algorithm.” 2007. Thesis, Hong Kong University of Science and Technology. Accessed January 20, 2021. http://repository.ust.hk/ir/Record/1783.1-5471 ; https://doi.org/10.14711/thesis-b987302 ; http://repository.ust.hk/ir/bitstream/1783.1-5471/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Law, Nga Lam. “Parameter-free adaptive genetic algorithm.” 2007. Web. 20 Jan 2021.

Vancouver:

Law NL. Parameter-free adaptive genetic algorithm. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2007. [cited 2021 Jan 20]. Available from: http://repository.ust.hk/ir/Record/1783.1-5471 ; https://doi.org/10.14711/thesis-b987302 ; http://repository.ust.hk/ir/bitstream/1783.1-5471/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Law NL. Parameter-free adaptive genetic algorithm. [Thesis]. Hong Kong University of Science and Technology; 2007. Available from: http://repository.ust.hk/ir/Record/1783.1-5471 ; https://doi.org/10.14711/thesis-b987302 ; http://repository.ust.hk/ir/bitstream/1783.1-5471/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Michigan State University

24. Buyukbozkirli, Bulent. Modeling genetic algorithm dynamics for OneMax and deceptive functions.

Degree: PhD, Department of Mathematics, 2004, Michigan State University

URL: http://etd.lib.msu.edu/islandora/object/etd:32812

Subjects/Keywords: Genetic algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Buyukbozkirli, B. (2004). Modeling genetic algorithm dynamics for OneMax and deceptive functions. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:32812

Chicago Manual of Style (16^th Edition):

Buyukbozkirli, Bulent. “Modeling genetic algorithm dynamics for OneMax and deceptive functions.” 2004. Doctoral Dissertation, Michigan State University. Accessed January 20, 2021. http://etd.lib.msu.edu/islandora/object/etd:32812.

MLA Handbook (7^th Edition):

Buyukbozkirli, Bulent. “Modeling genetic algorithm dynamics for OneMax and deceptive functions.” 2004. Web. 20 Jan 2021.

Vancouver:

Buyukbozkirli B. Modeling genetic algorithm dynamics for OneMax and deceptive functions. [Internet] [Doctoral dissertation]. Michigan State University; 2004. [cited 2021 Jan 20]. Available from: http://etd.lib.msu.edu/islandora/object/etd:32812.

Council of Science Editors:

Buyukbozkirli B. Modeling genetic algorithm dynamics for OneMax and deceptive functions. [Doctoral Dissertation]. Michigan State University; 2004. Available from: http://etd.lib.msu.edu/islandora/object/etd:32812

Michigan State University

25. Pei, Huafeng. A comparison of cohort GA with canonical serial and island-model distributed GA's.

Degree: MS, Department of Electrical and Computer Engineering, 2000, Michigan State University

URL: http://etd.lib.msu.edu/islandora/object/etd:30589

Subjects/Keywords: Genetic algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Pei, H. (2000). A comparison of cohort GA with canonical serial and island-model distributed GA's. (Masters Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:30589

Chicago Manual of Style (16^th Edition):

Pei, Huafeng. “A comparison of cohort GA with canonical serial and island-model distributed GA's.” 2000. Masters Thesis, Michigan State University. Accessed January 20, 2021. http://etd.lib.msu.edu/islandora/object/etd:30589.

MLA Handbook (7^th Edition):

Pei, Huafeng. “A comparison of cohort GA with canonical serial and island-model distributed GA's.” 2000. Web. 20 Jan 2021.

Vancouver:

Pei H. A comparison of cohort GA with canonical serial and island-model distributed GA's. [Internet] [Masters thesis]. Michigan State University; 2000. [cited 2021 Jan 20]. Available from: http://etd.lib.msu.edu/islandora/object/etd:30589.

Council of Science Editors:

Pei H. A comparison of cohort GA with canonical serial and island-model distributed GA's. [Masters Thesis]. Michigan State University; 2000. Available from: http://etd.lib.msu.edu/islandora/object/etd:30589

Montana State University

26. Hayes, Christina Savannah Maria. Generic properties of the infinite population genetic algorithm.

Degree: PhD, College of Letters & Science, 2006, Montana State University

URL: https://scholarworks.montana.edu/xmlui/handle/1/1448

► The infinite population model for the genetic algorithm, where the iteration of the genetic algorithm corresponds to an iteration of a map G, is a… (more)

Subjects/Keywords: Genetic algorithms.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Hayes, C. S. M. (2006). Generic properties of the infinite population genetic algorithm. (Doctoral Dissertation). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/1448

Chicago Manual of Style (16^th Edition):

Hayes, Christina Savannah Maria. “Generic properties of the infinite population genetic algorithm.” 2006. Doctoral Dissertation, Montana State University. Accessed January 20, 2021. https://scholarworks.montana.edu/xmlui/handle/1/1448.

MLA Handbook (7^th Edition):

Hayes, Christina Savannah Maria. “Generic properties of the infinite population genetic algorithm.” 2006. Web. 20 Jan 2021.

Vancouver:

Hayes CSM. Generic properties of the infinite population genetic algorithm. [Internet] [Doctoral dissertation]. Montana State University; 2006. [cited 2021 Jan 20]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/1448.

Council of Science Editors:

Hayes CSM. Generic properties of the infinite population genetic algorithm. [Doctoral Dissertation]. Montana State University; 2006. Available from: https://scholarworks.montana.edu/xmlui/handle/1/1448

Montana State University

27. Pamplin, Trenton L. Hybridizing statistics with genetic algorithms.

Degree: MS, College of Letters & Science, 1995, Montana State University

URL: https://scholarworks.montana.edu/xmlui/handle/1/7586

Subjects/Keywords: Genetic algorithms.

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APA (6^th Edition):

Pamplin, T. L. (1995). Hybridizing statistics with genetic algorithms. (Masters Thesis). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/7586

Chicago Manual of Style (16^th Edition):

Pamplin, Trenton L. “Hybridizing statistics with genetic algorithms.” 1995. Masters Thesis, Montana State University. Accessed January 20, 2021. https://scholarworks.montana.edu/xmlui/handle/1/7586.

MLA Handbook (7^th Edition):

Pamplin, Trenton L. “Hybridizing statistics with genetic algorithms.” 1995. Web. 20 Jan 2021.

Vancouver:

Pamplin TL. Hybridizing statistics with genetic algorithms. [Internet] [Masters thesis]. Montana State University; 1995. [cited 2021 Jan 20]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/7586.

Council of Science Editors:

Pamplin TL. Hybridizing statistics with genetic algorithms. [Masters Thesis]. Montana State University; 1995. Available from: https://scholarworks.montana.edu/xmlui/handle/1/7586

University of Missouri – Columbia

28. Shi, Zhuoqun. Improved genetic algorithm for distribution system performance analysis.

Degree: 2017, University of Missouri – Columbia

URL: http://hdl.handle.net/10355/62087

► The incipient smart grid initiative and increasing use of distributed generation, along with classical problems of distribution system reconfiguration and restoration (DSR), have led to… (more)

▼ The incipient smart grid initiative and increasing use of distributed generation, along with classical problems of distribution system reconfiguration and restoration (DSR), have led to the need for efficient and reliable power distribution system simulation tools. One recently developed tool, the Fast Non-dominated Sorting Genetic Algorithm, or FNSGA, has been shown to be very effective at finding Pareto optimal distribution systems that are optimized with respect to voltages, currents, and power losses. Despite its promise, the FNSGA has two shortcomings, which are addressed in this thesis. The first is that it uses a load flow sub-program (to determine voltages, currents, and losses throughout the power system in question) that is based on the classical Newton-Raphson numerical analytical approach. For a variety of reasons, the Newton-Raphson method often encounters convergence problems when applied to distribution (rather than transmission) systems, and it has burdensome memory and CPU time requirements when applied to large systems. In this thesis, the Newton-Raphson load flow program is replaced in the FNSGA with a revised version of the so-called direct method, the principal revision being a coded novel scheme for properly, rapidly, and repeatedly re-numbering the busses and branches in the power system for load flow analysis within the FNSGA. Validation results for the described scheme are presented by comparing results obtained with it and with the Newton-Raphson-based load flow scheme. The principal difference between the two methods is that the computation time is significantly reduced with the revised direct load flow method. The second shortcoming of the FNSGA to be addressed here is that it is not optimized for certain important parameters, namely the initial population size N and the number of generations Gen, which could lead to excessive CPU time requirements. In this thesis, a parametric study was conducted to determine minimum values of N and Gen that lead to reasonably repeatable configurations of a distribution system that are optimized for the multiple objectives of voltages (in the voltage profiles), currents (in the system load balancing index), and power losses. Studies conducted on 16- and 32-bus test systems revealed that, to produce repeatable solution sets in the 16-bus system, optimum values of N and Gen are small enough that CPU times are very small. However, in the 32-bus system, N and Gen need to be so large that CPU times become prohibitive. Presumably, the problem would get worse with even larger systems. Fortunately, a solution to this problem was found, which involves removing certain branches from the pool of possibilities when producing the initial population N in the genetic algorithm. Disqualified branches are those determined in preliminary simulations to never appear in Pareto optimal solution sets. This method was shown to be very effective at leading to small enough optimum values of N and Gen that CPU times are reasonable. Advisors/Committee Members: O'Connell, Robert (advisor).

Subjects/Keywords: Genetic algorithms; Performance – Analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Shi, Z. (2017). Improved genetic algorithm for distribution system performance analysis. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/62087

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Shi, Zhuoqun. “Improved genetic algorithm for distribution system performance analysis.” 2017. Thesis, University of Missouri – Columbia. Accessed January 20, 2021. http://hdl.handle.net/10355/62087.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Shi, Zhuoqun. “Improved genetic algorithm for distribution system performance analysis.” 2017. Web. 20 Jan 2021.

Vancouver:

Shi Z. Improved genetic algorithm for distribution system performance analysis. [Internet] [Thesis]. University of Missouri – Columbia; 2017. [cited 2021 Jan 20]. Available from: http://hdl.handle.net/10355/62087.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shi Z. Improved genetic algorithm for distribution system performance analysis. [Thesis]. University of Missouri – Columbia; 2017. Available from: http://hdl.handle.net/10355/62087

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. Henshall, Gareth. Optimising kinematic systems using crowd-sourcing and genetic algorithms.

Degree: PhD, 2019, Bangor University

URL: https://research.bangor.ac.uk/portal/en/theses/optimising-kinematic-systems-using-crowdsourcing-and-genetic-algorithms(788570df-afc1-49d6-abad-965cf8370d6d).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782099

► Procedural animation systems are capable of synthesising life-like organic motion automatically. However due to extensive parameterisation, tuning these systems can be very difficult. Not only… (more)

Subjects/Keywords: optimisation; crowd-sourcing; genetic algorithms

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APA (6^th Edition):

Henshall, G. (2019). Optimising kinematic systems using crowd-sourcing and genetic algorithms. (Doctoral Dissertation). Bangor University. Retrieved from https://research.bangor.ac.uk/portal/en/theses/optimising-kinematic-systems-using-crowdsourcing-and-genetic-algorithms(788570df-afc1-49d6-abad-965cf8370d6d).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782099

Chicago Manual of Style (16^th Edition):

Henshall, Gareth. “Optimising kinematic systems using crowd-sourcing and genetic algorithms.” 2019. Doctoral Dissertation, Bangor University. Accessed January 20, 2021. https://research.bangor.ac.uk/portal/en/theses/optimising-kinematic-systems-using-crowdsourcing-and-genetic-algorithms(788570df-afc1-49d6-abad-965cf8370d6d).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782099.

MLA Handbook (7^th Edition):

Henshall, Gareth. “Optimising kinematic systems using crowd-sourcing and genetic algorithms.” 2019. Web. 20 Jan 2021.

Vancouver:

Henshall G. Optimising kinematic systems using crowd-sourcing and genetic algorithms. [Internet] [Doctoral dissertation]. Bangor University; 2019. [cited 2021 Jan 20]. Available from: https://research.bangor.ac.uk/portal/en/theses/optimising-kinematic-systems-using-crowdsourcing-and-genetic-algorithms(788570df-afc1-49d6-abad-965cf8370d6d).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782099.

Council of Science Editors:

Henshall G. Optimising kinematic systems using crowd-sourcing and genetic algorithms. [Doctoral Dissertation]. Bangor University; 2019. Available from: https://research.bangor.ac.uk/portal/en/theses/optimising-kinematic-systems-using-crowdsourcing-and-genetic-algorithms(788570df-afc1-49d6-abad-965cf8370d6d).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782099

University of New South Wales

30. Chi, Tzi-Chieh. Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles.

Degree: Mechanical & Manufacturing Engineering, 2015, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/54276 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:34575/SOURCE02?view=true

► Evolving swarms have advantages over monolithic vehicles in a number of situations. They are able to distribute their sensors more widely, require less sophistication and… (more)

▼ Evolving swarms have advantages over monolithic vehicles in a number of situations. They are able to distribute their sensors more widely, require less sophistication and are robust in that the failure of one element leads to the degradation of the swarm rather than complete failure. Significant benefits of these characteristics include greater endurance and the ability to operate in dangerous environments.Two applications were developed in this thesis to investigate the technological feasibility of an ever evolving swarm in different technological areas. While one part, of the research, explored the ruggedness bestowed on a space system in a debris field by using distributed agents the other looked at how their performance could be improved in a much simpler scenario by using evolutionary algorithms. The aims of this thesis are to explore the feasibility of using an evolutionary method to develop the rules governing self-organised systems to coordinate and control swarms of satellites in debris avoidance manoeuvres and UAVs in marine search and rescue (SAR) missions. The proposed models are capable of improving the energy efficiency of two different methods by which a cluster of spacecraft can perform a scatter and re-gather manoeuvre to rapidly avoid collision with space debris; as well as allowing SAR co-ordinators to better manage their man-power and resources for an increased chance of target identification within a desired timeframe.A swarm intelligent model was developed and implemented using the agent-based software, NetLogo© for SAR missions. The model used self-organised emergent behaviour with an evolutionary algorithm to optimise the effectiveness of the swarm in adapting to changing environments. The spacecraft debris avoidance case study model was developed in Matlab and validated by comparing it with a STK / Astrogator generated ephemeris 3D model within an orbital environment simulator. The elliptic formation validated through STK was able to achieve the same performance in Matlab in a continuous and nonlinear model through incorporating J2 perturbations.The results show a swarm-intelligence based approach is effective, robust and scalable. Both of the developed scattering manoeuvres were able to maintain the desired cluster flight formation in J2 perturbations with Δv optimised to minimise fuel consumption. In addition, the SAR UAVs demonstrated the ability to form teams, fly in formation and find the targets with only initial human input required being to generate a fitness factor; with results showing that there is an effective division of labour. Advisors/Committee Members: Page, John, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW, Olsen, John, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW, Tsafnat, Naomi, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW.

Subjects/Keywords: Genetic Algorithms; Swarm; Self-Organising

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chi, T. (2015). Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/54276 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:34575/SOURCE02?view=true

Chicago Manual of Style (16^th Edition):

Chi, Tzi-Chieh. “Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles.” 2015. Masters Thesis, University of New South Wales. Accessed January 20, 2021. http://handle.unsw.edu.au/1959.4/54276 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:34575/SOURCE02?view=true.

MLA Handbook (7^th Edition):

Chi, Tzi-Chieh. “Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles.” 2015. Web. 20 Jan 2021.

Vancouver:

Chi T. Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles. [Internet] [Masters thesis]. University of New South Wales; 2015. [cited 2021 Jan 20]. Available from: http://handle.unsw.edu.au/1959.4/54276 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:34575/SOURCE02?view=true.

Council of Science Editors:

Chi T. Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles. [Masters Thesis]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/54276 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:34575/SOURCE02?view=true

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Open Access Theses and Dissertations