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You searched for +publisher:"North Dakota State University" +contributor:("Ludwig, Simone"). Showing records 1 – 24 of 24 total matches.

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1. [No author]. Optimization of Deployments for Service Oriented Clouds.

Degree: 2015, North Dakota State University

 In cloud-computing environments, every service in an application is deployed as a different service instance. All service instances are deployed at a different level of… (more)

Subjects/Keywords: Cloud computing.; Quality of service (Computer networks); Application software.

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

APA (6th Edition):

author], [. (2015). Optimization of Deployments for Service Oriented Clouds. (Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25484

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):

author], [No. “Optimization of Deployments for Service Oriented Clouds.” 2015. Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25484.

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

MLA Handbook (7th Edition):

author], [No. “Optimization of Deployments for Service Oriented Clouds.” 2015. Web. 22 May 2018.

Vancouver:

author] [. Optimization of Deployments for Service Oriented Clouds. [Internet] [Thesis]. North Dakota State University; 2015. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25484.

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

Council of Science Editors:

author] [. Optimization of Deployments for Service Oriented Clouds. [Thesis]. North Dakota State University; 2015. Available from: http://hdl.handle.net/10365/25484

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

2. [No author]. Implementation of Particle Swarm Optimization Based Fuzzy Clustering Approach to Identify Optimum Number of Clusters.

Degree: 2015, North Dakota State University

 One versatile and popular method for the clustering analysis is fuzzy clustering. This clustering method allows the individual data points to belong to more than… (more)

Subjects/Keywords: Fuzzy sets.; Mathematical optimization.; Swarm intelligence.; Cluster analysis.

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APA (6th Edition):

author], [. (2015). Implementation of Particle Swarm Optimization Based Fuzzy Clustering Approach to Identify Optimum Number of Clusters. (Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25486

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):

author], [No. “Implementation of Particle Swarm Optimization Based Fuzzy Clustering Approach to Identify Optimum Number of Clusters.” 2015. Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25486.

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

MLA Handbook (7th Edition):

author], [No. “Implementation of Particle Swarm Optimization Based Fuzzy Clustering Approach to Identify Optimum Number of Clusters.” 2015. Web. 22 May 2018.

Vancouver:

author] [. Implementation of Particle Swarm Optimization Based Fuzzy Clustering Approach to Identify Optimum Number of Clusters. [Internet] [Thesis]. North Dakota State University; 2015. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25486.

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

Council of Science Editors:

author] [. Implementation of Particle Swarm Optimization Based Fuzzy Clustering Approach to Identify Optimum Number of Clusters. [Thesis]. North Dakota State University; 2015. Available from: http://hdl.handle.net/10365/25486

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

3. [No author]. Evaluating Fitness of Patch-Based Terrains in the Use of Video Games.

Degree: 2017, North Dakota State University

 This paper deals with current an existing evolutionary algorithm used in procedural terrain generation content for video games which is gaining interest to lessen the… (more)

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APA (6th Edition):

author], [. (2017). Evaluating Fitness of Patch-Based Terrains in the Use of Video Games. (Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25948

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):

author], [No. “Evaluating Fitness of Patch-Based Terrains in the Use of Video Games.” 2017. Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25948.

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

MLA Handbook (7th Edition):

author], [No. “Evaluating Fitness of Patch-Based Terrains in the Use of Video Games.” 2017. Web. 22 May 2018.

Vancouver:

author] [. Evaluating Fitness of Patch-Based Terrains in the Use of Video Games. [Internet] [Thesis]. North Dakota State University; 2017. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25948.

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

Council of Science Editors:

author] [. Evaluating Fitness of Patch-Based Terrains in the Use of Video Games. [Thesis]. North Dakota State University; 2017. Available from: http://hdl.handle.net/10365/25948

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

4. [No author]. Evaluation of a New Bio-Inspired Algorithm: Krill Herd.

Degree: 2014, North Dakota State University

 Number of nature inspired algorithms is proposed to solve complex optimization problems. The Krill Herd algorithm is one such biologically-inspired algorithm, proposed to solve optimization… (more)

Subjects/Keywords: Biologically-inspired computing.; Swarm intelligence.; Mathematical optimization.

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APA (6th Edition):

author], [. (2014). Evaluation of a New Bio-Inspired Algorithm: Krill Herd. (Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/24754

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):

author], [No. “Evaluation of a New Bio-Inspired Algorithm: Krill Herd.” 2014. Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/24754.

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

MLA Handbook (7th Edition):

author], [No. “Evaluation of a New Bio-Inspired Algorithm: Krill Herd.” 2014. Web. 22 May 2018.

Vancouver:

author] [. Evaluation of a New Bio-Inspired Algorithm: Krill Herd. [Internet] [Thesis]. North Dakota State University; 2014. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/24754.

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

Council of Science Editors:

author] [. Evaluation of a New Bio-Inspired Algorithm: Krill Herd. [Thesis]. North Dakota State University; 2014. Available from: http://hdl.handle.net/10365/24754

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

5. [No author]. Particle Swarm Optimization Algorithm: Variants and Comparisons.

Degree: 2015, North Dakota State University

 Since the introduction of Particle Swarm optimization by Dr. Eberhart and Dr. Kennedy, there have been many variations of the algorithm proposed by many researchers… (more)

Subjects/Keywords: Swarm intelligence.; Mathematical optimization.; Problem solving.; Algorithms.

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APA (6th Edition):

author], [. (2015). Particle Swarm Optimization Algorithm: Variants and Comparisons. (Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25404

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):

author], [No. “Particle Swarm Optimization Algorithm: Variants and Comparisons.” 2015. Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25404.

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

MLA Handbook (7th Edition):

author], [No. “Particle Swarm Optimization Algorithm: Variants and Comparisons.” 2015. Web. 22 May 2018.

Vancouver:

author] [. Particle Swarm Optimization Algorithm: Variants and Comparisons. [Internet] [Thesis]. North Dakota State University; 2015. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25404.

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

Council of Science Editors:

author] [. Particle Swarm Optimization Algorithm: Variants and Comparisons. [Thesis]. North Dakota State University; 2015. Available from: http://hdl.handle.net/10365/25404

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

6. [No author]. Applied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approaches.

Degree: 2014, North Dakota State University

 Recently, in many experimental studies, the statistical analysis of nonparametric comparisons has grown in the area of computational intelligence. The research refers to application of… (more)

Subjects/Keywords: Computational intelligence.; Swarm intelligence.; Evolutionary computation.; Nonparametric statistics.; Mathematical optimization.

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APA (6th Edition):

author], [. (2014). Applied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approaches. (Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/23144

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):

author], [No. “Applied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approaches.” 2014. Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/23144.

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

MLA Handbook (7th Edition):

author], [No. “Applied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approaches.” 2014. Web. 22 May 2018.

Vancouver:

author] [. Applied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approaches. [Internet] [Thesis]. North Dakota State University; 2014. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/23144.

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

Council of Science Editors:

author] [. Applied Nonparametric Statistical Tests to Compare Evolutionary and Swarm Intelligence Approaches. [Thesis]. North Dakota State University; 2014. Available from: http://hdl.handle.net/10365/23144

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

7. Madamanchi, Manoj Babu. Parallelization of Generic PSO Java Code Using MPJExpress.

Degree: MS, Computer Science, 2013, North Dakota State University

 Many scientific, engineering and economic problems involve the optimization of a set of parameters. The Particle Swarm Optimization (PSO) is one of the new techniques… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2013.; Parallel algorithms.; Swarm intelligence.; Mathematical optimization.

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APA (6th Edition):

Madamanchi, M. B. (2013). Parallelization of Generic PSO Java Code Using MPJExpress. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/22571

Chicago Manual of Style (16th Edition):

Madamanchi, Manoj Babu. “Parallelization of Generic PSO Java Code Using MPJExpress.” 2013. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/22571.

MLA Handbook (7th Edition):

Madamanchi, Manoj Babu. “Parallelization of Generic PSO Java Code Using MPJExpress.” 2013. Web. 22 May 2018.

Vancouver:

Madamanchi MB. Parallelization of Generic PSO Java Code Using MPJExpress. [Internet] [Masters thesis]. North Dakota State University; 2013. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/22571.

Council of Science Editors:

Madamanchi MB. Parallelization of Generic PSO Java Code Using MPJExpress. [Masters Thesis]. North Dakota State University; 2013. Available from: http://hdl.handle.net/10365/22571

8. Nayakam, GhanaShyam Nath. Study of Similarity Coefficients Using MapReduce Programming Model.

Degree: MS, Computer Science, 2013, North Dakota State University

 MapReduce is a programming model for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2013.; Computer algorithms.; Data mining.; Big data.; MapReduce (Computer file)

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APA (6th Edition):

Nayakam, G. N. (2013). Study of Similarity Coefficients Using MapReduce Programming Model. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/22599

Chicago Manual of Style (16th Edition):

Nayakam, GhanaShyam Nath. “Study of Similarity Coefficients Using MapReduce Programming Model.” 2013. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/22599.

MLA Handbook (7th Edition):

Nayakam, GhanaShyam Nath. “Study of Similarity Coefficients Using MapReduce Programming Model.” 2013. Web. 22 May 2018.

Vancouver:

Nayakam GN. Study of Similarity Coefficients Using MapReduce Programming Model. [Internet] [Masters thesis]. North Dakota State University; 2013. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/22599.

Council of Science Editors:

Nayakam GN. Study of Similarity Coefficients Using MapReduce Programming Model. [Masters Thesis]. North Dakota State University; 2013. Available from: http://hdl.handle.net/10365/22599

9. Barat, Debarshi. Job Scheduling with Genetic Algorithm.

Degree: MS, Computer Science, 2013, North Dakota State University

 In this paper, we have used a Genetic Algorithm (GA) approach for providing a solution to the Job Scheduling Problem (JSP) of placing 5000 jobs… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2013.; Production scheduling.; Genetic algorithms.

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APA (6th Edition):

Barat, D. (2013). Job Scheduling with Genetic Algorithm. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/22775

Chicago Manual of Style (16th Edition):

Barat, Debarshi. “Job Scheduling with Genetic Algorithm.” 2013. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/22775.

MLA Handbook (7th Edition):

Barat, Debarshi. “Job Scheduling with Genetic Algorithm.” 2013. Web. 22 May 2018.

Vancouver:

Barat D. Job Scheduling with Genetic Algorithm. [Internet] [Masters thesis]. North Dakota State University; 2013. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/22775.

Council of Science Editors:

Barat D. Job Scheduling with Genetic Algorithm. [Masters Thesis]. North Dakota State University; 2013. Available from: http://hdl.handle.net/10365/22775

10. Dandu, Naveen Kumar. Optimization of Benchmark Functions using Chemical Reaction Optimization.

Degree: MS, Computer Science, 2013, North Dakota State University

 In recent past, many new nature-inspired optimization techniques have been emerged in the field of science and engineering that have proven to be efficient to… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2013.; Mathematical optimization.; Chemical reactions.; Heuristic algorithms.

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APA (6th Edition):

Dandu, N. K. (2013). Optimization of Benchmark Functions using Chemical Reaction Optimization. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/22782

Chicago Manual of Style (16th Edition):

Dandu, Naveen Kumar. “Optimization of Benchmark Functions using Chemical Reaction Optimization.” 2013. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/22782.

MLA Handbook (7th Edition):

Dandu, Naveen Kumar. “Optimization of Benchmark Functions using Chemical Reaction Optimization.” 2013. Web. 22 May 2018.

Vancouver:

Dandu NK. Optimization of Benchmark Functions using Chemical Reaction Optimization. [Internet] [Masters thesis]. North Dakota State University; 2013. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/22782.

Council of Science Editors:

Dandu NK. Optimization of Benchmark Functions using Chemical Reaction Optimization. [Masters Thesis]. North Dakota State University; 2013. Available from: http://hdl.handle.net/10365/22782

11. Kundur, Anuroop. Evaluation of Firefly Algorithm Using Benchmark Functions.

Degree: MS, Computer Science, 2013, North Dakota State University

 The field of nature inspired computing and optimization techniques have evolved to solve the difficult optimization problems in diverse fields of engineering, science and technology.… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2013.; Heuristic algorithms  – Evaluation.; Mathematical optimization.; Swarm intelligence.

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APA (6th Edition):

Kundur, A. (2013). Evaluation of Firefly Algorithm Using Benchmark Functions. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/23076

Chicago Manual of Style (16th Edition):

Kundur, Anuroop. “Evaluation of Firefly Algorithm Using Benchmark Functions.” 2013. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/23076.

MLA Handbook (7th Edition):

Kundur, Anuroop. “Evaluation of Firefly Algorithm Using Benchmark Functions.” 2013. Web. 22 May 2018.

Vancouver:

Kundur A. Evaluation of Firefly Algorithm Using Benchmark Functions. [Internet] [Masters thesis]. North Dakota State University; 2013. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/23076.

Council of Science Editors:

Kundur A. Evaluation of Firefly Algorithm Using Benchmark Functions. [Masters Thesis]. North Dakota State University; 2013. Available from: http://hdl.handle.net/10365/23076

12. Dawar, Deepak. Real Parameter Optimization Using Differential Evolution.

Degree: MS, Computer Science, 2013, North Dakota State University

 Over recent years, Evolutionary Algorithms (EA) have emerged as a practical approach to solve hard optimization problems presented in real life. The inherent advantage of… (more)

Subjects/Keywords: Computer algorithms.; Evolution equations.; Stochastic processes  – Computer programs.; Evolution equations.; Mathematical optimization.; Master of Science / Computer Science, College of Science and Mathematics, 2013.

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APA (6th Edition):

Dawar, D. (2013). Real Parameter Optimization Using Differential Evolution. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/23101

Chicago Manual of Style (16th Edition):

Dawar, Deepak. “Real Parameter Optimization Using Differential Evolution.” 2013. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/23101.

MLA Handbook (7th Edition):

Dawar, Deepak. “Real Parameter Optimization Using Differential Evolution.” 2013. Web. 22 May 2018.

Vancouver:

Dawar D. Real Parameter Optimization Using Differential Evolution. [Internet] [Masters thesis]. North Dakota State University; 2013. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/23101.

Council of Science Editors:

Dawar D. Real Parameter Optimization Using Differential Evolution. [Masters Thesis]. North Dakota State University; 2013. Available from: http://hdl.handle.net/10365/23101

13. Sambaraju, Sharath Chandra. Historical Analysis and Estimation Tool for Energy Trading.

Degree: MS, Computer Science, 2014, North Dakota State University

 Many forms of commodities are traded in today’s financial world, the most commonly used commodity, ‘Electricity’, is no exception. Electricity is mostly traded on a… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2014.; Electric power  – Marketing.; Relational databases.; C# (Computer program language); SQL (Computer program language)

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APA (6th Edition):

Sambaraju, S. C. (2014). Historical Analysis and Estimation Tool for Energy Trading. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/23153

Chicago Manual of Style (16th Edition):

Sambaraju, Sharath Chandra. “Historical Analysis and Estimation Tool for Energy Trading.” 2014. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/23153.

MLA Handbook (7th Edition):

Sambaraju, Sharath Chandra. “Historical Analysis and Estimation Tool for Energy Trading.” 2014. Web. 22 May 2018.

Vancouver:

Sambaraju SC. Historical Analysis and Estimation Tool for Energy Trading. [Internet] [Masters thesis]. North Dakota State University; 2014. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/23153.

Council of Science Editors:

Sambaraju SC. Historical Analysis and Estimation Tool for Energy Trading. [Masters Thesis]. North Dakota State University; 2014. Available from: http://hdl.handle.net/10365/23153

14. Gadiparthi, Sudheer. Implementation of a Medical Decision Making Tool.

Degree: MS, Computer Science, 2014, North Dakota State University

 Nowadays timely medical assistance is necessary for physicians/medical practitioners for decision making. Sometimes it is necessary for physicians to make decisions to diagnose the disease… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2014.; Computer software.; Data mining.; Medical personnel  – Decision making  – Data processing.; Medical care  – Decision making  – Data processing.

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APA (6th Edition):

Gadiparthi, S. (2014). Implementation of a Medical Decision Making Tool. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/23164

Chicago Manual of Style (16th Edition):

Gadiparthi, Sudheer. “Implementation of a Medical Decision Making Tool.” 2014. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/23164.

MLA Handbook (7th Edition):

Gadiparthi, Sudheer. “Implementation of a Medical Decision Making Tool.” 2014. Web. 22 May 2018.

Vancouver:

Gadiparthi S. Implementation of a Medical Decision Making Tool. [Internet] [Masters thesis]. North Dakota State University; 2014. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/23164.

Council of Science Editors:

Gadiparthi S. Implementation of a Medical Decision Making Tool. [Masters Thesis]. North Dakota State University; 2014. Available from: http://hdl.handle.net/10365/23164

15. Gebremariam, Alemayehu. Graphical Simulation for Unmanned Aerial Vehicle Mission.

Degree: MS, Computer Science, 2014, North Dakota State University

 Unmanned Aerial Vehicles (UAVs) are automated flying planes currently focused on military and civilian applications. This work simulates the motion of UAV in the battlefield… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2014.; Drone aircraft  – Control systems  – Computer simulation.; Uninhabited combat aerial vehicles.; Digital computer simulation.

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APA (6th Edition):

Gebremariam, A. (2014). Graphical Simulation for Unmanned Aerial Vehicle Mission. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/23981

Chicago Manual of Style (16th Edition):

Gebremariam, Alemayehu. “Graphical Simulation for Unmanned Aerial Vehicle Mission.” 2014. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/23981.

MLA Handbook (7th Edition):

Gebremariam, Alemayehu. “Graphical Simulation for Unmanned Aerial Vehicle Mission.” 2014. Web. 22 May 2018.

Vancouver:

Gebremariam A. Graphical Simulation for Unmanned Aerial Vehicle Mission. [Internet] [Masters thesis]. North Dakota State University; 2014. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/23981.

Council of Science Editors:

Gebremariam A. Graphical Simulation for Unmanned Aerial Vehicle Mission. [Masters Thesis]. North Dakota State University; 2014. Available from: http://hdl.handle.net/10365/23981

16. Zheng, Songtao. Naïve Bayes Classifier: A MapReduce Approach.

Degree: MS, Computer Science, 2014, North Dakota State University

 Machine learning algorithms have the advantage of making use of the powerful Hadoop distributed computing platform and the MapReduce programming model to process data in… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2014.; Bayesian statistical decision theory.; Big data.; Machine learning.; Apache Hadoop.; MapReduce (Computer file)

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APA (6th Edition):

Zheng, S. (2014). Naïve Bayes Classifier: A MapReduce Approach. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/24752

Chicago Manual of Style (16th Edition):

Zheng, Songtao. “Naïve Bayes Classifier: A MapReduce Approach.” 2014. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/24752.

MLA Handbook (7th Edition):

Zheng, Songtao. “Naïve Bayes Classifier: A MapReduce Approach.” 2014. Web. 22 May 2018.

Vancouver:

Zheng S. Naïve Bayes Classifier: A MapReduce Approach. [Internet] [Masters thesis]. North Dakota State University; 2014. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/24752.

Council of Science Editors:

Zheng S. Naïve Bayes Classifier: A MapReduce Approach. [Masters Thesis]. North Dakota State University; 2014. Available from: http://hdl.handle.net/10365/24752

17. Valluru, Srikanth. Implementation of a Clonal Selection Algorithm.

Degree: MS, Computer Science, 2014, North Dakota State University

 Some of the best optimization solutions were inspired by nature. Clonal selection algorithm is a technique that was inspired from genetic behavior of the immune… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2014.; Artificial immune systems.; Immune system  – Computer simulation.; Evolutionary computation.; Algorithms.; Mathematical optimization.

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APA (6th Edition):

Valluru, S. (2014). Implementation of a Clonal Selection Algorithm. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/24759

Chicago Manual of Style (16th Edition):

Valluru, Srikanth. “Implementation of a Clonal Selection Algorithm.” 2014. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/24759.

MLA Handbook (7th Edition):

Valluru, Srikanth. “Implementation of a Clonal Selection Algorithm.” 2014. Web. 22 May 2018.

Vancouver:

Valluru S. Implementation of a Clonal Selection Algorithm. [Internet] [Masters thesis]. North Dakota State University; 2014. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/24759.

Council of Science Editors:

Valluru S. Implementation of a Clonal Selection Algorithm. [Masters Thesis]. North Dakota State University; 2014. Available from: http://hdl.handle.net/10365/24759

18. Bhattacharyya, Krittika. A Map Reduce Approach of K-Means++ Algorithm with Initial Equidistant Centers.

Degree: MS, Computer Science, 2015, North Dakota State University

 Data clustering has been received considerable attention in many applications, such as data mining, document retrieval, image segmentation and pattern classification. The enlarging volumes of… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2015.; Cluster analysis.; Big data.; Computer algorithms.

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APA (6th Edition):

Bhattacharyya, K. (2015). A Map Reduce Approach of K-Means++ Algorithm with Initial Equidistant Centers. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25350

Chicago Manual of Style (16th Edition):

Bhattacharyya, Krittika. “A Map Reduce Approach of K-Means++ Algorithm with Initial Equidistant Centers.” 2015. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25350.

MLA Handbook (7th Edition):

Bhattacharyya, Krittika. “A Map Reduce Approach of K-Means++ Algorithm with Initial Equidistant Centers.” 2015. Web. 22 May 2018.

Vancouver:

Bhattacharyya K. A Map Reduce Approach of K-Means++ Algorithm with Initial Equidistant Centers. [Internet] [Masters thesis]. North Dakota State University; 2015. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25350.

Council of Science Editors:

Bhattacharyya K. A Map Reduce Approach of K-Means++ Algorithm with Initial Equidistant Centers. [Masters Thesis]. North Dakota State University; 2015. Available from: http://hdl.handle.net/10365/25350

19. Gagganapalli, Srikanth Reddy. Implementation and Evaluation of CMA-ES Algorithm.

Degree: MS, Computer Science, 2015, North Dakota State University

 Over recent years, Evolutionary Algorithms have emerged as a practical approach to solve hard optimization problems in the fields of Science and Technology. The inherent… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2015.; Evolutionary computation.; Analysis of covariance.; Mathematical optimization.

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APA (6th Edition):

Gagganapalli, S. R. (2015). Implementation and Evaluation of CMA-ES Algorithm. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25507

Chicago Manual of Style (16th Edition):

Gagganapalli, Srikanth Reddy. “Implementation and Evaluation of CMA-ES Algorithm.” 2015. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25507.

MLA Handbook (7th Edition):

Gagganapalli, Srikanth Reddy. “Implementation and Evaluation of CMA-ES Algorithm.” 2015. Web. 22 May 2018.

Vancouver:

Gagganapalli SR. Implementation and Evaluation of CMA-ES Algorithm. [Internet] [Masters thesis]. North Dakota State University; 2015. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25507.

Council of Science Editors:

Gagganapalli SR. Implementation and Evaluation of CMA-ES Algorithm. [Masters Thesis]. North Dakota State University; 2015. Available from: http://hdl.handle.net/10365/25507

20. Moparthi, Rashmi. Speed Optimized Implementation of Ant Colony Optimization Algorithm for Image Edge Detection.

Degree: MS, Computer Science, 2016, North Dakota State University

 Ant Colony algorithm (ACO) is an approach used to provide a solution to an optimization problem. ACO follows the mechanism adapted by Ants to search… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2016.; MATLAB.; Computer algorithms.; Mathematical optimization.; Image processing.; Swarm intelligence.

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APA (6th Edition):

Moparthi, R. (2016). Speed Optimized Implementation of Ant Colony Optimization Algorithm for Image Edge Detection. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25557

Chicago Manual of Style (16th Edition):

Moparthi, Rashmi. “Speed Optimized Implementation of Ant Colony Optimization Algorithm for Image Edge Detection.” 2016. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25557.

MLA Handbook (7th Edition):

Moparthi, Rashmi. “Speed Optimized Implementation of Ant Colony Optimization Algorithm for Image Edge Detection.” 2016. Web. 22 May 2018.

Vancouver:

Moparthi R. Speed Optimized Implementation of Ant Colony Optimization Algorithm for Image Edge Detection. [Internet] [Masters thesis]. North Dakota State University; 2016. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25557.

Council of Science Editors:

Moparthi R. Speed Optimized Implementation of Ant Colony Optimization Algorithm for Image Edge Detection. [Masters Thesis]. North Dakota State University; 2016. Available from: http://hdl.handle.net/10365/25557

21. Kasam, Shashi Kanth. Glowworm Swarm Optimization Algorithm for Multi-Threshold Image Segmentation.

Degree: MS, Computer Science, 2016, North Dakota State University

 Glowworm Smarm Optimization (GSO), one of the nature-inspired swarm intelligence algorithms is used for finding solutions to optimization problems. Glowworms emit light to attract its… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2016.; Evolutionary programming (Computer science); Image processing  – Mathematics.; Swarm intelligence.; Mathematical optimization.; Genetic algorithms.; Heuristic algorithms.

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APA (6th Edition):

Kasam, S. K. (2016). Glowworm Swarm Optimization Algorithm for Multi-Threshold Image Segmentation. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25558

Chicago Manual of Style (16th Edition):

Kasam, Shashi Kanth. “Glowworm Swarm Optimization Algorithm for Multi-Threshold Image Segmentation.” 2016. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25558.

MLA Handbook (7th Edition):

Kasam, Shashi Kanth. “Glowworm Swarm Optimization Algorithm for Multi-Threshold Image Segmentation.” 2016. Web. 22 May 2018.

Vancouver:

Kasam SK. Glowworm Swarm Optimization Algorithm for Multi-Threshold Image Segmentation. [Internet] [Masters thesis]. North Dakota State University; 2016. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25558.

Council of Science Editors:

Kasam SK. Glowworm Swarm Optimization Algorithm for Multi-Threshold Image Segmentation. [Masters Thesis]. North Dakota State University; 2016. Available from: http://hdl.handle.net/10365/25558

22. Ghosh, Priyanka Singh. Parallelization of Particle Swarm Optimization Algorithm Using Hadoop Mapreduce.

Degree: MS, Computer Science, 2016, North Dakota State University

 Particle Swarm Optimization (PSO) has received attention in many research fields and real-world applications for solving optimization problems in the areas of intelligent transportation systems,… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2016.; Apache Hadoop.; Computer algorithms.; Mathematical optimization.; Swarm intelligence.; Parallel processing (Electronic computers)  – Programming.

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APA (6th Edition):

Ghosh, P. S. (2016). Parallelization of Particle Swarm Optimization Algorithm Using Hadoop Mapreduce. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25566

Chicago Manual of Style (16th Edition):

Ghosh, Priyanka Singh. “Parallelization of Particle Swarm Optimization Algorithm Using Hadoop Mapreduce.” 2016. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25566.

MLA Handbook (7th Edition):

Ghosh, Priyanka Singh. “Parallelization of Particle Swarm Optimization Algorithm Using Hadoop Mapreduce.” 2016. Web. 22 May 2018.

Vancouver:

Ghosh PS. Parallelization of Particle Swarm Optimization Algorithm Using Hadoop Mapreduce. [Internet] [Masters thesis]. North Dakota State University; 2016. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25566.

Council of Science Editors:

Ghosh PS. Parallelization of Particle Swarm Optimization Algorithm Using Hadoop Mapreduce. [Masters Thesis]. North Dakota State University; 2016. Available from: http://hdl.handle.net/10365/25566

23. Manne, Priyanka. Parallel Particle Swarm Optimization.

Degree: MS, Computer Science, 2016, North Dakota State University

 PSO is a population based evolutionary algorithm and is motivated from the simulation of social behavior, which differs from the natural selection scheme of genetic… (more)

Subjects/Keywords: Master of Science / Computer Science, College of Science and Mathematics, 2016.; MATLAB.; Computer algorithms.; Mathematical optimization.; Swarm intelligence.; Parallel processing (Electronic computers) – Programming.

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APA (6th Edition):

Manne, P. (2016). Parallel Particle Swarm Optimization. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/25649

Chicago Manual of Style (16th Edition):

Manne, Priyanka. “Parallel Particle Swarm Optimization.” 2016. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/25649.

MLA Handbook (7th Edition):

Manne, Priyanka. “Parallel Particle Swarm Optimization.” 2016. Web. 22 May 2018.

Vancouver:

Manne P. Parallel Particle Swarm Optimization. [Internet] [Masters thesis]. North Dakota State University; 2016. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/25649.

Council of Science Editors:

Manne P. Parallel Particle Swarm Optimization. [Masters Thesis]. North Dakota State University; 2016. Available from: http://hdl.handle.net/10365/25649

24. Daggubati, Satyanarayana. Comparison of Particle Swarm Optimization Variants.

Degree: MS, Computer Science, 2012, North Dakota State University

 Particle swarm optimization (PSO) is a heuristic global optimization method, which is based on swarm intelligence. It is inspired by the research on the bird… (more)

Subjects/Keywords: Master of Science / Computer Science; College of Science and Mathematics; 2012.

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APA (6th Edition):

Daggubati, S. (2012). Comparison of Particle Swarm Optimization Variants. (Masters Thesis). North Dakota State University. Retrieved from http://hdl.handle.net/10365/22285

Chicago Manual of Style (16th Edition):

Daggubati, Satyanarayana. “Comparison of Particle Swarm Optimization Variants.” 2012. Masters Thesis, North Dakota State University. Accessed May 22, 2018. http://hdl.handle.net/10365/22285.

MLA Handbook (7th Edition):

Daggubati, Satyanarayana. “Comparison of Particle Swarm Optimization Variants.” 2012. Web. 22 May 2018.

Vancouver:

Daggubati S. Comparison of Particle Swarm Optimization Variants. [Internet] [Masters thesis]. North Dakota State University; 2012. [cited 2018 May 22]. Available from: http://hdl.handle.net/10365/22285.

Council of Science Editors:

Daggubati S. Comparison of Particle Swarm Optimization Variants. [Masters Thesis]. North Dakota State University; 2012. Available from: http://hdl.handle.net/10365/22285

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