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You searched for subject:(Genetic Algorithms). Showing records 1 – 30 of 1486 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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Satishkumar MV. Simultaneous scheduling of machines and Agvs using evolutionary optimization algorithms. [Internet] [Thesis]. Jawaharlal Nehru Technological University; 2010. [cited 2020 Nov 25]. 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


Ryerson University

2. 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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Hajipour Y. Non-periodic inspection of optimization of repairable systems. [Internet] [Thesis]. Ryerson University; 2016. [cited 2020 Nov 25]. 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


Rochester Institute of Technology

3. 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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Lamos-Sweeney J. Deep learning using genetic algorithms. [Internet] [Thesis]. Rochester Institute of Technology; 2012. [cited 2020 Nov 25]. Available from: https://scholarworks.rit.edu/theses/254.

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

Council of Science Editors:

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

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


University of Alberta

4. 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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Shu L. The impact of data structures on the performance of genetic-algorithm-based learning. [Internet] [Doctoral dissertation]. University of Alberta; 1992. [cited 2020 Nov 25]. 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

5. 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 (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 November 25, 2020. 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. 25 Nov 2020.

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 2020 Nov 25]. Available from: http://hdl.handle.net/1969.1/159121.

Council of Science Editors:

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


Texas A&M University

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

Degree: MS, Petroleum Engineering, 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. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399

Chicago Manual of Style (16th Edition):

Gibbs, Trevor Howard. “Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms.” 2011. Masters Thesis, Texas A&M University. Accessed November 25, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399.

MLA Handbook (7th Edition):

Gibbs, Trevor Howard. “Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms.” 2011. Web. 25 Nov 2020.

Vancouver:

Gibbs TH. Horizontal Well Placement Optimization in Gas Reservoirs Using Genetic Algorithms. [Internet] [Masters thesis]. Texas A&M University; 2011. [cited 2020 Nov 25]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-399.

Council of Science Editors:

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


Nelson Mandela Metropolitan University

7. 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 November 25, 2020. 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. 25 Nov 2020.

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 2020 Nov 25]. Available from: http://hdl.handle.net/10948/d1008356.

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

Council of Science Editors:

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

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


Oregon State University

8. 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 (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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Dill KM. Growing digital circuits : logic synthesis and minimization with genetic operators. [Internet] [Masters thesis]. Oregon State University; 1996. [cited 2020 Nov 25]. 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

9. 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 November 25, 2020. http://hdl.handle.net/1957/34323.

MLA Handbook (7th Edition):

Canpolat, Necati. “Optimization of seasonal irrigation scheduling by genetic algorithms.” 1997. Web. 25 Nov 2020.

Vancouver:

Canpolat N. Optimization of seasonal irrigation scheduling by genetic algorithms. [Internet] [Doctoral dissertation]. Oregon State University; 1997. [cited 2020 Nov 25]. Available from: http://hdl.handle.net/1957/34323.

Council of Science Editors:

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


University of Guelph

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

Degree: PhD, School of Computer Science, 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. (Doctoral Dissertation). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793

Chicago Manual of Style (16th Edition):

Brown, Joseph Alexander. “Regression and Classification from Extinction.” 2014. Doctoral Dissertation, University of Guelph. Accessed November 25, 2020. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793.

MLA Handbook (7th Edition):

Brown, Joseph Alexander. “Regression and Classification from Extinction.” 2014. Web. 25 Nov 2020.

Vancouver:

Brown JA. Regression and Classification from Extinction. [Internet] [Doctoral dissertation]. University of Guelph; 2014. [cited 2020 Nov 25]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/7793.

Council of Science Editors:

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


University of Adelaide

11. 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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Sullivan ND. Task Allocation and Collaborative Localisation in Multi-Robot Systems. [Internet] [Thesis]. University of Adelaide; 2019. [cited 2020 Nov 25]. Available from: http://hdl.handle.net/2440/120578.

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

Council of Science Editors:

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

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


Chapman University

12. 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 November 25, 2020. https://digitalcommons.chapman.edu/cads_dissertations/1.

MLA Handbook (7th Edition):

James, Kevin. “Estimating Auction Equilibria using Individual Evolutionary Learning.” 2019. Web. 25 Nov 2020.

Vancouver:

James K. Estimating Auction Equilibria using Individual Evolutionary Learning. [Internet] [Doctoral dissertation]. Chapman University; 2019. [cited 2020 Nov 25]. Available from: https://digitalcommons.chapman.edu/cads_dissertations/1.

Council of Science Editors:

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


Hong Kong University of Science and Technology

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

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

Chicago Manual of Style (16th Edition):

Law, Nga Lam. “Parameter-free adaptive genetic algorithm.” 2007. Thesis, Hong Kong University of Science and Technology. Accessed November 25, 2020. http://repository.ust.hk/ir/Record/1783.1-5471 ; https://doi.org/10.14711/thesis-b987302 ; http://repository.ust.hk/ir/bitstream/1783.1-5471/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Law, Nga Lam. “Parameter-free adaptive genetic algorithm.” 2007. Web. 25 Nov 2020.

Vancouver:

Law NL. Parameter-free adaptive genetic algorithm. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2007. [cited 2020 Nov 25]. Available from: http://repository.ust.hk/ir/Record/1783.1-5471 ; https://doi.org/10.14711/thesis-b987302 ; http://repository.ust.hk/ir/bitstream/1783.1-5471/1/th_redirect.html.

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

Council of Science Editors:

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

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


Michigan State University

14. 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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Buyukbozkirli B. Modeling genetic algorithm dynamics for OneMax and deceptive functions. [Internet] [Doctoral dissertation]. Michigan State University; 2004. [cited 2020 Nov 25]. Available from: http://etd.lib.msu.edu/islandora/object/etd:32812.

Council of Science Editors:

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


Michigan State University

15. 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 November 25, 2020. 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. 25 Nov 2020.

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 2020 Nov 25]. 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

16. 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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Henshall G. Optimising kinematic systems using crowd-sourcing and genetic algorithms. [Internet] [Doctoral dissertation]. Bangor University; 2019. [cited 2020 Nov 25]. 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


Montana State University

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

Degree: PhD, 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 · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Hayes, Christina Savannah Maria. “Generic properties of the infinite population genetic algorithm.” 2006. Doctoral Dissertation, Montana State University. Accessed November 25, 2020. https://scholarworks.montana.edu/xmlui/handle/1/1448.

MLA Handbook (7th Edition):

Hayes, Christina Savannah Maria. “Generic properties of the infinite population genetic algorithm.” 2006. Web. 25 Nov 2020.

Vancouver:

Hayes CSM. Generic properties of the infinite population genetic algorithm. [Internet] [Doctoral dissertation]. Montana State University; 2006. [cited 2020 Nov 25]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/1448.

Council of Science Editors:

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


Montana State University

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

Degree: MS, 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. (Masters Thesis). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/7586

Chicago Manual of Style (16th Edition):

Pamplin, Trenton L. “Hybridizing statistics with genetic algorithms.” 1995. Masters Thesis, Montana State University. Accessed November 25, 2020. https://scholarworks.montana.edu/xmlui/handle/1/7586.

MLA Handbook (7th Edition):

Pamplin, Trenton L. “Hybridizing statistics with genetic algorithms.” 1995. Web. 25 Nov 2020.

Vancouver:

Pamplin TL. Hybridizing statistics with genetic algorithms. [Internet] [Masters thesis]. Montana State University; 1995. [cited 2020 Nov 25]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/7586.

Council of Science Editors:

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


University of Missouri – Columbia

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

Degree: 2017, University of Missouri – Columbia

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

Subjects/Keywords: Genetic algorithms; Performance – Analysis

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

APA (6th Edition):

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

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

Chicago Manual of Style (16th Edition):

Shi, Zhuoqun. “Improved genetic algorithm for distribution system performance analysis.” 2017. Thesis, University of Missouri – Columbia. Accessed November 25, 2020. http://hdl.handle.net/10355/62087.

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

MLA Handbook (7th Edition):

Shi, Zhuoqun. “Improved genetic algorithm for distribution system performance analysis.” 2017. Web. 25 Nov 2020.

Vancouver:

Shi Z. Improved genetic algorithm for distribution system performance analysis. [Internet] [Thesis]. University of Missouri – Columbia; 2017. [cited 2020 Nov 25]. Available from: http://hdl.handle.net/10355/62087.

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

Council of Science Editors:

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

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


University of New South Wales

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

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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Chi T. Evolutionary adaptation and optimisation in heterogeneous and homogeneous aerial search vehicles. [Internet] [Masters thesis]. University of New South Wales; 2015. [cited 2020 Nov 25]. 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


University of Oklahoma

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

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 November 25, 2020. 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. 25 Nov 2020.

Vancouver:

Carlson B. Phenotype Operators for Improved Performance of Heuristic Encoding Within Genetic Algorithms. [Internet] [Doctoral dissertation]. University of Oklahoma; 2016. [cited 2020 Nov 25]. 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


Ryerson University

22. Jirasek, Lubomir. A genetic algorithm based partition generation and optimization method for finite element problems.

Degree: 2009, Ryerson University

 A two-step partitioning algorithm for FE meshes is proposed in this work for the purposes of time savings. A direct method based on the concept… (more)

Subjects/Keywords: Genetic algorithms; Genetic programming (Computer science)

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

APA (6th Edition):

Jirasek, L. (2009). A genetic algorithm based partition generation and optimization method for finite element problems. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A1387

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):

Jirasek, Lubomir. “A genetic algorithm based partition generation and optimization method for finite element problems.” 2009. Thesis, Ryerson University. Accessed November 25, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A1387.

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

MLA Handbook (7th Edition):

Jirasek, Lubomir. “A genetic algorithm based partition generation and optimization method for finite element problems.” 2009. Web. 25 Nov 2020.

Vancouver:

Jirasek L. A genetic algorithm based partition generation and optimization method for finite element problems. [Internet] [Thesis]. Ryerson University; 2009. [cited 2020 Nov 25]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1387.

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

Council of Science Editors:

Jirasek L. A genetic algorithm based partition generation and optimization method for finite element problems. [Thesis]. Ryerson University; 2009. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A1387

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


Ryerson University

23. Gebremariam, Michael. Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm.

Degree: 2010, Ryerson University

 The objective of this project is to develop a software tool which assists in comparison of a work known as "M-GenESys: Multi Structure Genetic Algorithm… (more)

Subjects/Keywords: Genetic programming (Computer science); Genetic algorithms

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APA (6th Edition):

Gebremariam, M. (2010). Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A6075

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):

Gebremariam, Michael. “Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm.” 2010. Thesis, Ryerson University. Accessed November 25, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A6075.

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

MLA Handbook (7th Edition):

Gebremariam, Michael. “Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm.” 2010. Web. 25 Nov 2020.

Vancouver:

Gebremariam M. Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm. [Internet] [Thesis]. Ryerson University; 2010. [cited 2020 Nov 25]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A6075.

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

Council of Science Editors:

Gebremariam M. Implementation of integrated design space exploration of scheduling, allocation and binding in high level synthesis using multi structure genetic algorithm. [Thesis]. Ryerson University; 2010. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A6075

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


University of Stirling

24. Oaken, David R. Optimisation of Definition Structures & Parameter Values in Process Algebra Models Using Evolutionary Computation.

Degree: PhD, 2014, University of Stirling

 Process Algebras are a Formal Modelling methodology which are an effective tool for defining models of complex systems, particularly those involving multiple interacting processes. However,… (more)

Subjects/Keywords: genetic algorithms; process algebra; genetic programming; optimisation; Genetic algorithms; Algebra; Genetic programming (Computer science); Optimisation

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

APA (6th Edition):

Oaken, D. R. (2014). Optimisation of Definition Structures & Parameter Values in Process Algebra Models Using Evolutionary Computation. (Doctoral Dissertation). University of Stirling. Retrieved from http://hdl.handle.net/1893/21206

Chicago Manual of Style (16th Edition):

Oaken, David R. “Optimisation of Definition Structures & Parameter Values in Process Algebra Models Using Evolutionary Computation.” 2014. Doctoral Dissertation, University of Stirling. Accessed November 25, 2020. http://hdl.handle.net/1893/21206.

MLA Handbook (7th Edition):

Oaken, David R. “Optimisation of Definition Structures & Parameter Values in Process Algebra Models Using Evolutionary Computation.” 2014. Web. 25 Nov 2020.

Vancouver:

Oaken DR. Optimisation of Definition Structures & Parameter Values in Process Algebra Models Using Evolutionary Computation. [Internet] [Doctoral dissertation]. University of Stirling; 2014. [cited 2020 Nov 25]. Available from: http://hdl.handle.net/1893/21206.

Council of Science Editors:

Oaken DR. Optimisation of Definition Structures & Parameter Values in Process Algebra Models Using Evolutionary Computation. [Doctoral Dissertation]. University of Stirling; 2014. Available from: http://hdl.handle.net/1893/21206


University of Stirling

25. Neumann, Geoffrey K. TEDA: A Targeted Estimation of Distribution Algorithm.

Degree: PhD, School of Natural Sciences, 2014, University of Stirling

 This thesis discusses the development and performance of a novel evolutionary algorithm, the Targeted Estimation of Distribution Algorithm (TEDA). TEDA takes the concept of targeting,… (more)

Subjects/Keywords: Evolutionary Algorithms; Genetic Algorithms; Estimation of Distribution Algorithms; Targeting; TEDA; FDC; Distribution (Probability theory); Genetic algorithms; Algorithms

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

APA (6th Edition):

Neumann, G. K. (2014). TEDA: A Targeted Estimation of Distribution Algorithm. (Doctoral Dissertation). University of Stirling. Retrieved from http://hdl.handle.net/1893/20248

Chicago Manual of Style (16th Edition):

Neumann, Geoffrey K. “TEDA: A Targeted Estimation of Distribution Algorithm.” 2014. Doctoral Dissertation, University of Stirling. Accessed November 25, 2020. http://hdl.handle.net/1893/20248.

MLA Handbook (7th Edition):

Neumann, Geoffrey K. “TEDA: A Targeted Estimation of Distribution Algorithm.” 2014. Web. 25 Nov 2020.

Vancouver:

Neumann GK. TEDA: A Targeted Estimation of Distribution Algorithm. [Internet] [Doctoral dissertation]. University of Stirling; 2014. [cited 2020 Nov 25]. Available from: http://hdl.handle.net/1893/20248.

Council of Science Editors:

Neumann GK. TEDA: A Targeted Estimation of Distribution Algorithm. [Doctoral Dissertation]. University of Stirling; 2014. Available from: http://hdl.handle.net/1893/20248

26. Hafnaoui, Imane. Multimodal biometric fusion using evolutionary techniques.

Degree: 2014, Université M'Hamed Bougara Boumerdès

75 p. : ill. ; 30 cm

The work of this research focuses on fusing multiple biometric modalities at the score level using different combination… (more)

Subjects/Keywords: Genetic algorithms; Hybride; Fusion; Algorithmes génétiques

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

APA (6th Edition):

Hafnaoui, I. (2014). Multimodal biometric fusion using evolutionary techniques. (Thesis). Université M'Hamed Bougara Boumerdès. Retrieved from http://dlibrary.univ-boumerdes.dz:8080123456789/1592

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):

Hafnaoui, Imane. “Multimodal biometric fusion using evolutionary techniques.” 2014. Thesis, Université M'Hamed Bougara Boumerdès. Accessed November 25, 2020. http://dlibrary.univ-boumerdes.dz:8080123456789/1592.

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

MLA Handbook (7th Edition):

Hafnaoui, Imane. “Multimodal biometric fusion using evolutionary techniques.” 2014. Web. 25 Nov 2020.

Vancouver:

Hafnaoui I. Multimodal biometric fusion using evolutionary techniques. [Internet] [Thesis]. Université M'Hamed Bougara Boumerdès; 2014. [cited 2020 Nov 25]. Available from: http://dlibrary.univ-boumerdes.dz:8080123456789/1592.

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

Council of Science Editors:

Hafnaoui I. Multimodal biometric fusion using evolutionary techniques. [Thesis]. Université M'Hamed Bougara Boumerdès; 2014. Available from: http://dlibrary.univ-boumerdes.dz:8080123456789/1592

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

27. Brameier, Markus. On linear genetic programming.

Degree: 2004, Universität Dortmund

 The thesis is about linear genetic programming (LGP), a machine learning approach that evolves computer programs as sequences of imperative instructions. Two fundamental differences to… (more)

Subjects/Keywords: Evolutionary algorithms; Genetic programming; Machine learning; 004

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

APA (6th Edition):

Brameier, M. (2004). On linear genetic programming. (Thesis). Universität Dortmund. Retrieved from http://hdl.handle.net/2003/20098

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):

Brameier, Markus. “On linear genetic programming.” 2004. Thesis, Universität Dortmund. Accessed November 25, 2020. http://hdl.handle.net/2003/20098.

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

MLA Handbook (7th Edition):

Brameier, Markus. “On linear genetic programming.” 2004. Web. 25 Nov 2020.

Vancouver:

Brameier M. On linear genetic programming. [Internet] [Thesis]. Universität Dortmund; 2004. [cited 2020 Nov 25]. Available from: http://hdl.handle.net/2003/20098.

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

Council of Science Editors:

Brameier M. On linear genetic programming. [Thesis]. Universität Dortmund; 2004. Available from: http://hdl.handle.net/2003/20098

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


Ryerson University

28. Chan, Che-Hang Cliff. Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm.

Degree: 2003, Ryerson University

 The thesis presents a Genetic Algorithm with Adaptive Search Space (GAASS) proposed to improve both convergence performance and solution accuracy of traditional Genetic Algorithms(GAs). The… (more)

Subjects/Keywords: Genetic algorithms; Hysteresis

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APA (6th Edition):

Chan, C. C. (2003). Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A478

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):

Chan, Che-Hang Cliff. “Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm.” 2003. Thesis, Ryerson University. Accessed November 25, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A478.

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

MLA Handbook (7th Edition):

Chan, Che-Hang Cliff. “Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm.” 2003. Web. 25 Nov 2020.

Vancouver:

Chan CC. Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm. [Internet] [Thesis]. Ryerson University; 2003. [cited 2020 Nov 25]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A478.

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

Council of Science Editors:

Chan CC. Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm. [Thesis]. Ryerson University; 2003. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A478

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


Ryerson University

29. Sivapalan, Sanjeevan. A genetic algorithm approach to recommender system cold start problem.

Degree: 2015, Ryerson University

 Recommender systems (RS) are ubiquitous and used in many systems to augment user experience to improve usability and they achieve this by helping users discover… (more)

Subjects/Keywords: Recommender systems (Information filtering); Genetic algorithms.

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APA (6th Edition):

Sivapalan, S. (2015). A genetic algorithm approach to recommender system cold start problem. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A3664

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):

Sivapalan, Sanjeevan. “A genetic algorithm approach to recommender system cold start problem.” 2015. Thesis, Ryerson University. Accessed November 25, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A3664.

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

MLA Handbook (7th Edition):

Sivapalan, Sanjeevan. “A genetic algorithm approach to recommender system cold start problem.” 2015. Web. 25 Nov 2020.

Vancouver:

Sivapalan S. A genetic algorithm approach to recommender system cold start problem. [Internet] [Thesis]. Ryerson University; 2015. [cited 2020 Nov 25]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3664.

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

Council of Science Editors:

Sivapalan S. A genetic algorithm approach to recommender system cold start problem. [Thesis]. Ryerson University; 2015. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3664

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


Rochester Institute of Technology

30. Nogaj, Adam. Establishing parameters for problem difficulty in permutation-based genetic algorithms.

Degree: Computer Science (GCCIS), 2011, Rochester Institute of Technology

 This thesis examines the performance of genetic algorithm (GA) crossover techniques within two problems: n-queens with poison (NQWP) and processor scheduling (PS). Each problem was… (more)

Subjects/Keywords: Crossover; Genetic algorithms; N-queens; Processor scheduling

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APA (6th Edition):

Nogaj, A. (2011). Establishing parameters for problem difficulty in permutation-based genetic algorithms. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/252

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):

Nogaj, Adam. “Establishing parameters for problem difficulty in permutation-based genetic algorithms.” 2011. Thesis, Rochester Institute of Technology. Accessed November 25, 2020. https://scholarworks.rit.edu/theses/252.

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

MLA Handbook (7th Edition):

Nogaj, Adam. “Establishing parameters for problem difficulty in permutation-based genetic algorithms.” 2011. Web. 25 Nov 2020.

Vancouver:

Nogaj A. Establishing parameters for problem difficulty in permutation-based genetic algorithms. [Internet] [Thesis]. Rochester Institute of Technology; 2011. [cited 2020 Nov 25]. Available from: https://scholarworks.rit.edu/theses/252.

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

Council of Science Editors:

Nogaj A. Establishing parameters for problem difficulty in permutation-based genetic algorithms. [Thesis]. Rochester Institute of Technology; 2011. Available from: https://scholarworks.rit.edu/theses/252

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

[1] [2] [3] [4] [5] … [50]

.