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You searched for subject:(Genetic Algorithms). Showing records 1 – 30 of 1428 total matches.

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

Degree: 2010, Jawaharlal Nehru Technological University

 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 (6th 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 (16th Edition):

Satishkumar, M V. “Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms.” 2010. Thesis, Jawaharlal Nehru Technological University. Accessed October 15, 2019. 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 (7th Edition):

Satishkumar, M V. “Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms.” 2010. Web. 15 Oct 2019.

Vancouver:

Satishkumar MV. Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms. [Internet] [Thesis]. Jawaharlal Nehru Technological University; 2010. [cited 2019 Oct 15]. 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


Brunel University

2. Saud, Moudar. Convolution based real-time control strategy for vehicle active suspension systems.

Degree: PhD, 2009, Brunel University

 A novel real-time control method that minimises linear system vibrations when it is subjected to an arbitrary external excitation is proposed in this study. The… (more)

Subjects/Keywords: 629.2; Genetic algorithms

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APA (6th Edition):

Saud, M. (2009). Convolution based real-time control strategy for vehicle active suspension systems. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/6278 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549629

Chicago Manual of Style (16th Edition):

Saud, Moudar. “Convolution based real-time control strategy for vehicle active suspension systems.” 2009. Doctoral Dissertation, Brunel University. Accessed October 15, 2019. http://bura.brunel.ac.uk/handle/2438/6278 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549629.

MLA Handbook (7th Edition):

Saud, Moudar. “Convolution based real-time control strategy for vehicle active suspension systems.” 2009. Web. 15 Oct 2019.

Vancouver:

Saud M. Convolution based real-time control strategy for vehicle active suspension systems. [Internet] [Doctoral dissertation]. Brunel University; 2009. [cited 2019 Oct 15]. Available from: http://bura.brunel.ac.uk/handle/2438/6278 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549629.

Council of Science Editors:

Saud M. Convolution based real-time control strategy for vehicle active suspension systems. [Doctoral Dissertation]. Brunel University; 2009. Available from: http://bura.brunel.ac.uk/handle/2438/6278 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549629


Ryerson University

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

Degree: 2016, Ryerson University

 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)

Subjects/Keywords: Inspections; Genetic algorithms

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APA (6th 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 (16th Edition):

Hajipour, Yassin. “Non-periodic inspection of optimization of repairable systems.” 2016. Thesis, Ryerson University. Accessed October 15, 2019. 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 (7th Edition):

Hajipour, Yassin. “Non-periodic inspection of optimization of repairable systems.” 2016. Web. 15 Oct 2019.

Vancouver:

Hajipour Y. Non-periodic inspection of optimization of repairable systems. [Internet] [Thesis]. Ryerson University; 2016. [cited 2019 Oct 15]. 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


Montana State University

4. Richter, James Neal. On mutation and crossover in the theory of evolutionary algorithms.

Degree: College of Engineering, 2010, Montana State University

 The Evolutionary Algorithm is a population-based metaheuristic optimization algorithm. The EA employs mutation, crossover and selection operators inspired by biological evolution. It is commonly applied… (more)

Subjects/Keywords: Genetic algorithms.; Dynamics.

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APA (6th Edition):

Richter, J. N. (2010). On mutation and crossover in the theory of evolutionary algorithms. (Thesis). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/2132

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

Chicago Manual of Style (16th Edition):

Richter, James Neal. “On mutation and crossover in the theory of evolutionary algorithms.” 2010. Thesis, Montana State University. Accessed October 15, 2019. https://scholarworks.montana.edu/xmlui/handle/1/2132.

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

MLA Handbook (7th Edition):

Richter, James Neal. “On mutation and crossover in the theory of evolutionary algorithms.” 2010. Web. 15 Oct 2019.

Vancouver:

Richter JN. On mutation and crossover in the theory of evolutionary algorithms. [Internet] [Thesis]. Montana State University; 2010. [cited 2019 Oct 15]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/2132.

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

Council of Science Editors:

Richter JN. On mutation and crossover in the theory of evolutionary algorithms. [Thesis]. Montana State University; 2010. Available from: https://scholarworks.montana.edu/xmlui/handle/1/2132

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


University of Western Australia

5. Czarn, Andrew Simon Timothy. Statistical exploratory analysis of genetic algorithms.

Degree: PhD, 2008, University of Western Australia

 [Truncated abstract] Genetic algorithms (GAs) have been extensively used and studied in computer science, yet there is no generally accepted methodology for exploring which parameters… (more)

Subjects/Keywords: Genetic algorithms; Computer algorithms; Statistical analysis

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APA (6th Edition):

Czarn, A. S. T. (2008). Statistical exploratory analysis of genetic algorithms. (Doctoral Dissertation). University of Western Australia. Retrieved from http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=9580&local_base=GEN01-INS01

Chicago Manual of Style (16th Edition):

Czarn, Andrew Simon Timothy. “Statistical exploratory analysis of genetic algorithms.” 2008. Doctoral Dissertation, University of Western Australia. Accessed October 15, 2019. http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=9580&local_base=GEN01-INS01.

MLA Handbook (7th Edition):

Czarn, Andrew Simon Timothy. “Statistical exploratory analysis of genetic algorithms.” 2008. Web. 15 Oct 2019.

Vancouver:

Czarn AST. Statistical exploratory analysis of genetic algorithms. [Internet] [Doctoral dissertation]. University of Western Australia; 2008. [cited 2019 Oct 15]. Available from: http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=9580&local_base=GEN01-INS01.

Council of Science Editors:

Czarn AST. Statistical exploratory analysis of genetic algorithms. [Doctoral Dissertation]. University of Western Australia; 2008. Available from: http://repository.uwa.edu.au:80/R/?func=dbin-jump-full&object_id=9580&local_base=GEN01-INS01


University of Georgia

6. Wu, Lei. A comparison of nature inspired intelligent optimization methods in aerial spray deposition management.

Degree: MS, Artificial Intelligence, 2002, University of Georgia

 The AGDISP aerial spray simulation model is used to predict the deposition of spray material released from an aircraft. Determining the optimal input values to… (more)

Subjects/Keywords: Genetic Algorithms

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APA (6th Edition):

Wu, L. (2002). A comparison of nature inspired intelligent optimization methods in aerial spray deposition management. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/wu_lei_200212_ms

Chicago Manual of Style (16th Edition):

Wu, Lei. “A comparison of nature inspired intelligent optimization methods in aerial spray deposition management.” 2002. Masters Thesis, University of Georgia. Accessed October 15, 2019. http://purl.galileo.usg.edu/uga_etd/wu_lei_200212_ms.

MLA Handbook (7th Edition):

Wu, Lei. “A comparison of nature inspired intelligent optimization methods in aerial spray deposition management.” 2002. Web. 15 Oct 2019.

Vancouver:

Wu L. A comparison of nature inspired intelligent optimization methods in aerial spray deposition management. [Internet] [Masters thesis]. University of Georgia; 2002. [cited 2019 Oct 15]. Available from: http://purl.galileo.usg.edu/uga_etd/wu_lei_200212_ms.

Council of Science Editors:

Wu L. A comparison of nature inspired intelligent optimization methods in aerial spray deposition management. [Masters Thesis]. University of Georgia; 2002. Available from: http://purl.galileo.usg.edu/uga_etd/wu_lei_200212_ms


University of Georgia

7. Tariman, Kaan. Genetic algorithms for stochastic context-free grammar parameter estimation.

Degree: MS, Computer Science, 2004, University of Georgia

 Stochastic grammar models for biological sequences have been extensively used in secondary structure prediction and profiling for structural homology recognition. A pertinent issue is, given… (more)

Subjects/Keywords: genetic algorithms

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APA (6th Edition):

Tariman, K. (2004). Genetic algorithms for stochastic context-free grammar parameter estimation. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/tariman_kaan_200405_ms

Chicago Manual of Style (16th Edition):

Tariman, Kaan. “Genetic algorithms for stochastic context-free grammar parameter estimation.” 2004. Masters Thesis, University of Georgia. Accessed October 15, 2019. http://purl.galileo.usg.edu/uga_etd/tariman_kaan_200405_ms.

MLA Handbook (7th Edition):

Tariman, Kaan. “Genetic algorithms for stochastic context-free grammar parameter estimation.” 2004. Web. 15 Oct 2019.

Vancouver:

Tariman K. Genetic algorithms for stochastic context-free grammar parameter estimation. [Internet] [Masters thesis]. University of Georgia; 2004. [cited 2019 Oct 15]. Available from: http://purl.galileo.usg.edu/uga_etd/tariman_kaan_200405_ms.

Council of Science Editors:

Tariman K. Genetic algorithms for stochastic context-free grammar parameter estimation. [Masters Thesis]. University of Georgia; 2004. Available from: http://purl.galileo.usg.edu/uga_etd/tariman_kaan_200405_ms


University of Georgia

8. Chafekar, Deepti Ramesh. Multi-objective optimization using steady state genetic algorithms.

Degree: MS, Computer Science, 2004, University of Georgia

 There are many interesting problems in the real world that require multiple objectives to be satisfied at the same time. For many real world design… (more)

Subjects/Keywords: Genetic Algorithms

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APA (6th Edition):

Chafekar, D. R. (2004). Multi-objective optimization using steady state genetic algorithms. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/chafekar_deepti_r_200412_ms

Chicago Manual of Style (16th Edition):

Chafekar, Deepti Ramesh. “Multi-objective optimization using steady state genetic algorithms.” 2004. Masters Thesis, University of Georgia. Accessed October 15, 2019. http://purl.galileo.usg.edu/uga_etd/chafekar_deepti_r_200412_ms.

MLA Handbook (7th Edition):

Chafekar, Deepti Ramesh. “Multi-objective optimization using steady state genetic algorithms.” 2004. Web. 15 Oct 2019.

Vancouver:

Chafekar DR. Multi-objective optimization using steady state genetic algorithms. [Internet] [Masters thesis]. University of Georgia; 2004. [cited 2019 Oct 15]. Available from: http://purl.galileo.usg.edu/uga_etd/chafekar_deepti_r_200412_ms.

Council of Science Editors:

Chafekar DR. Multi-objective optimization using steady state genetic algorithms. [Masters Thesis]. University of Georgia; 2004. Available from: http://purl.galileo.usg.edu/uga_etd/chafekar_deepti_r_200412_ms


University of Georgia

9. Zhang, Chongshan. Improving GA performance by using Maximal Hyper-Rectangle analysis and relative fitness.

Degree: MS, Computer Science, 2005, University of Georgia

 In this thesis, we present two techniques to improve the performance of the genetic algorithm (GA). First we use Maximal Hyper-Rectangle (MHR) analysis to improve… (more)

Subjects/Keywords: Genetic Algorithms

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APA (6th Edition):

Zhang, C. (2005). Improving GA performance by using Maximal Hyper-Rectangle analysis and relative fitness. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/zhang_chongshan_200505_ms

Chicago Manual of Style (16th Edition):

Zhang, Chongshan. “Improving GA performance by using Maximal Hyper-Rectangle analysis and relative fitness.” 2005. Masters Thesis, University of Georgia. Accessed October 15, 2019. http://purl.galileo.usg.edu/uga_etd/zhang_chongshan_200505_ms.

MLA Handbook (7th Edition):

Zhang, Chongshan. “Improving GA performance by using Maximal Hyper-Rectangle analysis and relative fitness.” 2005. Web. 15 Oct 2019.

Vancouver:

Zhang C. Improving GA performance by using Maximal Hyper-Rectangle analysis and relative fitness. [Internet] [Masters thesis]. University of Georgia; 2005. [cited 2019 Oct 15]. Available from: http://purl.galileo.usg.edu/uga_etd/zhang_chongshan_200505_ms.

Council of Science Editors:

Zhang C. Improving GA performance by using Maximal Hyper-Rectangle analysis and relative fitness. [Masters Thesis]. University of Georgia; 2005. Available from: http://purl.galileo.usg.edu/uga_etd/zhang_chongshan_200505_ms


University of Georgia

10. Dewey, John Avery. Searching for prescriptive treatment schedules with a genetic algorithm: a tool for forest management.

Degree: MS, Artificial Intelligence, 2005, University of Georgia

 This thesis describes research on the use of a genetic algorithm (GA) to prescribe treatment plans for forest management at the stand level. Forest management… (more)

Subjects/Keywords: Genetic algorithms

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APA (6th Edition):

Dewey, J. A. (2005). Searching for prescriptive treatment schedules with a genetic algorithm: a tool for forest management. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/dewey_john_a_200508_ms

Chicago Manual of Style (16th Edition):

Dewey, John Avery. “Searching for prescriptive treatment schedules with a genetic algorithm: a tool for forest management.” 2005. Masters Thesis, University of Georgia. Accessed October 15, 2019. http://purl.galileo.usg.edu/uga_etd/dewey_john_a_200508_ms.

MLA Handbook (7th Edition):

Dewey, John Avery. “Searching for prescriptive treatment schedules with a genetic algorithm: a tool for forest management.” 2005. Web. 15 Oct 2019.

Vancouver:

Dewey JA. Searching for prescriptive treatment schedules with a genetic algorithm: a tool for forest management. [Internet] [Masters thesis]. University of Georgia; 2005. [cited 2019 Oct 15]. Available from: http://purl.galileo.usg.edu/uga_etd/dewey_john_a_200508_ms.

Council of Science Editors:

Dewey JA. Searching for prescriptive treatment schedules with a genetic algorithm: a tool for forest management. [Masters Thesis]. University of Georgia; 2005. Available from: http://purl.galileo.usg.edu/uga_etd/dewey_john_a_200508_ms


University of Alberta

11. 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

Subjects/Keywords: Genetic algorithms.

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APA (6th 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 (16th Edition):

Shu, Lingyan. “The impact of data structures on the performance of genetic-algorithm-based learning.” 1992. Doctoral Dissertation, University of Alberta. Accessed October 15, 2019. https://era.library.ualberta.ca/files/bg257h66m.

MLA Handbook (7th Edition):

Shu, Lingyan. “The impact of data structures on the performance of genetic-algorithm-based learning.” 1992. Web. 15 Oct 2019.

Vancouver:

Shu L. The impact of data structures on the performance of genetic-algorithm-based learning. [Internet] [Doctoral dissertation]. University of Alberta; 1992. [cited 2019 Oct 15]. 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

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

Degree: 2011, Texas A&M University

 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)

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

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Gibbs, Trevor Howard. “Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms.” 2011. Thesis, Texas A&M University. Accessed October 15, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399.

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

MLA Handbook (7th Edition):

Gibbs, Trevor Howard. “Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms.” 2011. Web. 15 Oct 2019.

Vancouver:

Gibbs TH. Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms. [Internet] [Thesis]. Texas A&M University; 2011. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399.

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

Council of Science Editors:

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

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


Hong Kong University of Science and Technology

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

Degree: 2007, Hong Kong University of Science and Technology

 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 (6th Edition):

Law, N. L. (2007). Parameter-free adaptive genetic algorithm. (Thesis). Hong Kong University of Science and Technology. Retrieved from 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 (16th Edition):

Law, Nga Lam. “Parameter-free adaptive genetic algorithm.” 2007. Thesis, Hong Kong University of Science and Technology. Accessed October 15, 2019. 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 (7th Edition):

Law, Nga Lam. “Parameter-free adaptive genetic algorithm.” 2007. Web. 15 Oct 2019.

Vancouver:

Law NL. Parameter-free adaptive genetic algorithm. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2007. [cited 2019 Oct 15]. Available from: 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: 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


University of Hong Kong

14. Liu, Xinyi. A general RNA secondary structure algorithm with vertical tree grammar.

Degree: M. Phil., 2013, University of Hong Kong

Our understanding of the functions played by RNA molecules is expanded with the understanding of RNA structures. Except for primary structure, RNA molecules present pairings… (more)

Subjects/Keywords: RNA - Structure; Genetic algorithms

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APA (6th Edition):

Liu, X. (2013). A general RNA secondary structure algorithm with vertical tree grammar. (Masters Thesis). University of Hong Kong. Retrieved from Liu, X. [刘欣怡]. (2013). A general RNA secondary structure algorithm with vertical tree grammar. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5177352 ; http://dx.doi.org/10.5353/th_b5177352 ; http://hdl.handle.net/10722/196439

Chicago Manual of Style (16th Edition):

Liu, Xinyi. “A general RNA secondary structure algorithm with vertical tree grammar.” 2013. Masters Thesis, University of Hong Kong. Accessed October 15, 2019. Liu, X. [刘欣怡]. (2013). A general RNA secondary structure algorithm with vertical tree grammar. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5177352 ; http://dx.doi.org/10.5353/th_b5177352 ; http://hdl.handle.net/10722/196439.

MLA Handbook (7th Edition):

Liu, Xinyi. “A general RNA secondary structure algorithm with vertical tree grammar.” 2013. Web. 15 Oct 2019.

Vancouver:

Liu X. A general RNA secondary structure algorithm with vertical tree grammar. [Internet] [Masters thesis]. University of Hong Kong; 2013. [cited 2019 Oct 15]. Available from: Liu, X. [刘欣怡]. (2013). A general RNA secondary structure algorithm with vertical tree grammar. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5177352 ; http://dx.doi.org/10.5353/th_b5177352 ; http://hdl.handle.net/10722/196439.

Council of Science Editors:

Liu X. A general RNA secondary structure algorithm with vertical tree grammar. [Masters Thesis]. University of Hong Kong; 2013. Available from: Liu, X. [刘欣怡]. (2013). A general RNA secondary structure algorithm with vertical tree grammar. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5177352 ; http://dx.doi.org/10.5353/th_b5177352 ; http://hdl.handle.net/10722/196439


University of Hong Kong

15. Li, Ping. Analysis and synthesis of positive systems and related gene network models.

Degree: PhD, 2011, University of Hong Kong

The Best PhD Thesis in the Faculties of Dentistry, Engineering, Medicine and Science (University of Hong Kong), Li Ka Shing Prize,2010-11

published_or_final_version

Mechanical Engineering

Doctoral

Doctor of Philosophy

Advisors/Committee Members: Lam, J.

Subjects/Keywords: Genetic algorithms.; Positive systems.

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APA (6th Edition):

Li, P. (2011). Analysis and synthesis of positive systems and related gene network models. (Doctoral Dissertation). University of Hong Kong. Retrieved from Li, P. [李平]. (2011). Analysis and synthesis of positive systems and related gene network models. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4658702 ; http://dx.doi.org/10.5353/th_b4658702 ; http://hdl.handle.net/10722/143209

Chicago Manual of Style (16th Edition):

Li, Ping. “Analysis and synthesis of positive systems and related gene network models.” 2011. Doctoral Dissertation, University of Hong Kong. Accessed October 15, 2019. Li, P. [李平]. (2011). Analysis and synthesis of positive systems and related gene network models. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4658702 ; http://dx.doi.org/10.5353/th_b4658702 ; http://hdl.handle.net/10722/143209.

MLA Handbook (7th Edition):

Li, Ping. “Analysis and synthesis of positive systems and related gene network models.” 2011. Web. 15 Oct 2019.

Vancouver:

Li P. Analysis and synthesis of positive systems and related gene network models. [Internet] [Doctoral dissertation]. University of Hong Kong; 2011. [cited 2019 Oct 15]. Available from: Li, P. [李平]. (2011). Analysis and synthesis of positive systems and related gene network models. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4658702 ; http://dx.doi.org/10.5353/th_b4658702 ; http://hdl.handle.net/10722/143209.

Council of Science Editors:

Li P. Analysis and synthesis of positive systems and related gene network models. [Doctoral Dissertation]. University of Hong Kong; 2011. Available from: Li, P. [李平]. (2011). Analysis and synthesis of positive systems and related gene network models. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4658702 ; http://dx.doi.org/10.5353/th_b4658702 ; http://hdl.handle.net/10722/143209


Texas A&M University

16. 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

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

APA (6th 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 (16th 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 October 15, 2019. http://hdl.handle.net/1969.1/159121.

MLA Handbook (7th Edition):

Kumar, Akansha. “An Iterative Optimization Method Using Genetic Algorithms and Gaussian Process Based Regression in Nuclear Reactor Design Applications.” 2016. Web. 15 Oct 2019.

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 2019 Oct 15]. 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


Montana State University

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

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

Subjects/Keywords: Genetic algorithms.

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APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Pamplin, Trenton L. “Hybridizing statistics with genetic algorithms.” 1995. Thesis, Montana State University. Accessed October 15, 2019. https://scholarworks.montana.edu/xmlui/handle/1/7586.

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

MLA Handbook (7th Edition):

Pamplin, Trenton L. “Hybridizing statistics with genetic algorithms.” 1995. Web. 15 Oct 2019.

Vancouver:

Pamplin TL. Hybridizing statistics with genetic algorithms. [Internet] [Thesis]. Montana State University; 1995. [cited 2019 Oct 15]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/7586.

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

Council of Science Editors:

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

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

 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)

Subjects/Keywords: Genetic algorithms

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

APA (6th 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 (16th Edition):

Dill, Karen M. “Growing digital circuits : logic synthesis and minimization with genetic operators.” 1996. Masters Thesis, Oregon State University. Accessed October 15, 2019. http://hdl.handle.net/1957/34241.

MLA Handbook (7th Edition):

Dill, Karen M. “Growing digital circuits : logic synthesis and minimization with genetic operators.” 1996. Web. 15 Oct 2019.

Vancouver:

Dill KM. Growing digital circuits : logic synthesis and minimization with genetic operators. [Internet] [Masters thesis]. Oregon State University; 1996. [cited 2019 Oct 15]. 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

 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)

Subjects/Keywords: Genetic algorithms

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APA (6th 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 (16th Edition):

Canpolat, Necati. “Optimization of seasonal irrigation scheduling by genetic algorithms.” 1997. Doctoral Dissertation, Oregon State University. Accessed October 15, 2019. http://hdl.handle.net/1957/34323.

MLA Handbook (7th Edition):

Canpolat, Necati. “Optimization of seasonal irrigation scheduling by genetic algorithms.” 1997. Web. 15 Oct 2019.

Vancouver:

Canpolat N. Optimization of seasonal irrigation scheduling by genetic algorithms. [Internet] [Doctoral dissertation]. Oregon State University; 1997. [cited 2019 Oct 15]. 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 Oklahoma

20. Carlson, Benjamin. Phenotype Operators for Improved Performance of Heuristic Encoding Within Genetic Algorithms.

Degree: PhD, 2016, University of Oklahoma

 Many approaches to applying Genetic Algorithms (GAs) to Nondeterministic Polynomial time Complete (NPC) problems involve population members encoded directly from the problem solution space. While… (more)

Subjects/Keywords: Heuristics; Genetic Algorithms; Evolutionary Computation

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APA (6th Edition):

Carlson, B. (2016). Phenotype Operators for Improved Performance of Heuristic Encoding Within Genetic Algorithms. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/34654

Chicago Manual of Style (16th Edition):

Carlson, Benjamin. “Phenotype Operators for Improved Performance of Heuristic Encoding Within Genetic Algorithms.” 2016. Doctoral Dissertation, University of Oklahoma. Accessed October 15, 2019. http://hdl.handle.net/11244/34654.

MLA Handbook (7th Edition):

Carlson, Benjamin. “Phenotype Operators for Improved Performance of Heuristic Encoding Within Genetic Algorithms.” 2016. Web. 15 Oct 2019.

Vancouver:

Carlson B. Phenotype Operators for Improved Performance of Heuristic Encoding Within Genetic Algorithms. [Internet] [Doctoral dissertation]. University of Oklahoma; 2016. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/11244/34654.

Council of Science Editors:

Carlson B. Phenotype Operators for Improved Performance of Heuristic Encoding Within Genetic Algorithms. [Doctoral Dissertation]. University of Oklahoma; 2016. Available from: http://hdl.handle.net/11244/34654


Nelson Mandela Metropolitan University

21. 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

 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 (6th 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 (16th Edition):

Buys, Stefan. “Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition.” 2012. Thesis, Nelson Mandela Metropolitan University. Accessed October 15, 2019. 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 (7th Edition):

Buys, Stefan. “Genetic algorithm for Artificial Neural Network training for the purpose of Automated Part Recognition.” 2012. Web. 15 Oct 2019.

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 2019 Oct 15]. 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


University of New South Wales

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

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

 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)

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

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APA (6th 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 (16th Edition):

Chi, Tzi-Chieh. “Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles.” 2015. Masters Thesis, University of New South Wales. Accessed October 15, 2019. http://handle.unsw.edu.au/1959.4/54276 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:34575/SOURCE02?view=true.

MLA Handbook (7th Edition):

Chi, Tzi-Chieh. “Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles.” 2015. Web. 15 Oct 2019.

Vancouver:

Chi T. Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles. [Internet] [Masters thesis]. University of New South Wales; 2015. [cited 2019 Oct 15]. 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


Rochester Institute of Technology

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

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

 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 (6th 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 (16th Edition):

Lamos-Sweeney, Joshua. “Deep learning using genetic algorithms.” 2012. Thesis, Rochester Institute of Technology. Accessed October 15, 2019. 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 (7th Edition):

Lamos-Sweeney, Joshua. “Deep learning using genetic algorithms.” 2012. Web. 15 Oct 2019.

Vancouver:

Lamos-Sweeney J. Deep learning using genetic algorithms. [Internet] [Thesis]. Rochester Institute of Technology; 2012. [cited 2019 Oct 15]. 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


Montana State University

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

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

 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 (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Hayes, Christina Savannah Maria. “Generic properties of the infinite population genetic algorithm.” 2006. Thesis, Montana State University. Accessed October 15, 2019. https://scholarworks.montana.edu/xmlui/handle/1/1448.

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

MLA Handbook (7th Edition):

Hayes, Christina Savannah Maria. “Generic properties of the infinite population genetic algorithm.” 2006. Web. 15 Oct 2019.

Vancouver:

Hayes CSM. Generic properties of the infinite population genetic algorithm. [Internet] [Thesis]. Montana State University; 2006. [cited 2019 Oct 15]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/1448.

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

Council of Science Editors:

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

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


Chapman University

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

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

  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 (6th 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 (16th Edition):

James, Kevin. “Estimating Auction Equilibria using Individual Evolutionary Learning.” 2019. Doctoral Dissertation, Chapman University. Accessed October 15, 2019. https://digitalcommons.chapman.edu/cads_dissertations/1.

MLA Handbook (7th Edition):

James, Kevin. “Estimating Auction Equilibria using Individual Evolutionary Learning.” 2019. Web. 15 Oct 2019.

Vancouver:

James K. Estimating Auction Equilibria using Individual Evolutionary Learning. [Internet] [Doctoral dissertation]. Chapman University; 2019. [cited 2019 Oct 15]. 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


University of Guelph

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

Degree: 2014, University of Guelph

 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 (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Brown, Joseph Alexander. “Regression and Classification from Extinction .” 2014. Thesis, University of Guelph. Accessed October 15, 2019. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793.

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

MLA Handbook (7th Edition):

Brown, Joseph Alexander. “Regression and Classification from Extinction .” 2014. Web. 15 Oct 2019.

Vancouver:

Brown JA. Regression and Classification from Extinction . [Internet] [Thesis]. University of Guelph; 2014. [cited 2019 Oct 15]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793.

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

Council of Science Editors:

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

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

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

Degree: PhD, 2019, Bangor University

 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 (6th 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 (16th Edition):

Henshall, Gareth. “Optimising kinematic systems using crowd-sourcing and genetic algorithms.” 2019. Doctoral Dissertation, Bangor University. Accessed October 15, 2019. 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 (7th Edition):

Henshall, Gareth. “Optimising kinematic systems using crowd-sourcing and genetic algorithms.” 2019. Web. 15 Oct 2019.

Vancouver:

Henshall G. Optimising kinematic systems using crowd-sourcing and genetic algorithms. [Internet] [Doctoral dissertation]. Bangor University; 2019. [cited 2019 Oct 15]. 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


Michigan State University

28. 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

Subjects/Keywords: Genetic algorithms

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APA (6th 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 (16th Edition):

Pei, Huafeng. “A comparison of cohort GA with canonical serial and island-model distributed GA's.” 2000. Masters Thesis, Michigan State University. Accessed October 15, 2019. http://etd.lib.msu.edu/islandora/object/etd:30589.

MLA Handbook (7th Edition):

Pei, Huafeng. “A comparison of cohort GA with canonical serial and island-model distributed GA's.” 2000. Web. 15 Oct 2019.

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 2019 Oct 15]. 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


Michigan State University

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

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

Subjects/Keywords: Genetic algorithms

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APA (6th 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 (16th Edition):

Buyukbozkirli, Bulent. “Modeling genetic algorithm dynamics for OneMax and deceptive functions.” 2004. Doctoral Dissertation, Michigan State University. Accessed October 15, 2019. http://etd.lib.msu.edu/islandora/object/etd:32812.

MLA Handbook (7th Edition):

Buyukbozkirli, Bulent. “Modeling genetic algorithm dynamics for OneMax and deceptive functions.” 2004. Web. 15 Oct 2019.

Vancouver:

Buyukbozkirli B. Modeling genetic algorithm dynamics for OneMax and deceptive functions. [Internet] [Doctoral dissertation]. Michigan State University; 2004. [cited 2019 Oct 15]. 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


University of Adelaide

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

Degree: 2019, University of Adelaide

 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)

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

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APA (6th 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 (16th Edition):

Sullivan, Nicholas David. “Task Allocation and Collaborative Localisation in Multi-Robot Systems.” 2019. Thesis, University of Adelaide. Accessed October 15, 2019. 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 (7th Edition):

Sullivan, Nicholas David. “Task Allocation and Collaborative Localisation in Multi-Robot Systems.” 2019. Web. 15 Oct 2019.

Vancouver:

Sullivan ND. Task Allocation and Collaborative Localisation in Multi-Robot Systems. [Internet] [Thesis]. University of Adelaide; 2019. [cited 2019 Oct 15]. 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

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