Gotowa bibliografia na temat „Genetic algorithms”
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Artykuły w czasopismach na temat "Genetic algorithms"
Sumida, Brian. "Genetics for genetic algorithms". ACM SIGBIO Newsletter 12, nr 2 (czerwiec 1992): 44–46. http://dx.doi.org/10.1145/130686.130694.
Pełny tekst źródłaRaol, Jitendra R., i Abhijit Jalisatgi. "From genetics to genetic algorithms". Resonance 1, nr 8 (sierpień 1996): 43–54. http://dx.doi.org/10.1007/bf02837022.
Pełny tekst źródłaBabu, M. Nishidhar, Y. Kiran i A. Ramesh V. Rajendra. "Tackling Real-Coded Genetic Algorithms". International Journal of Trend in Scientific Research and Development Volume-2, Issue-1 (31.12.2017): 217–23. http://dx.doi.org/10.31142/ijtsrd5905.
Pełny tekst źródłaAbbas, Basim K. "Genetic Algorithms for Quadratic Equations". Aug-Sept 2023, nr 35 (26.08.2023): 36–42. http://dx.doi.org/10.55529/jecnam.35.36.42.
Pełny tekst źródłaNico, Nico, Novrido Charibaldi i Yuli Fauziah. "Comparison of Memetic Algorithm and Genetic Algorithm on Nurse Picket Scheduling at Public Health Center". International Journal of Artificial Intelligence & Robotics (IJAIR) 4, nr 1 (30.05.2022): 9–23. http://dx.doi.org/10.25139/ijair.v4i1.4323.
Pełny tekst źródłaCarnahan, J., i R. Sinha. "Nature's algorithms [genetic algorithms]". IEEE Potentials 20, nr 2 (2001): 21–24. http://dx.doi.org/10.1109/45.954644.
Pełny tekst źródłaFrenzel, J. F. "Genetic algorithms". IEEE Potentials 12, nr 3 (październik 1993): 21–24. http://dx.doi.org/10.1109/45.282292.
Pełny tekst źródłaFulkerson, William F. "Genetic Algorithms". Journal of the American Statistical Association 97, nr 457 (marzec 2002): 366. http://dx.doi.org/10.1198/jasa.2002.s468.
Pełny tekst źródłaForrest, Stephanie. "Genetic algorithms". ACM Computing Surveys 28, nr 1 (marzec 1996): 77–80. http://dx.doi.org/10.1145/234313.234350.
Pełny tekst źródłaHolland, John H. "Genetic Algorithms". Scientific American 267, nr 1 (lipiec 1992): 66–72. http://dx.doi.org/10.1038/scientificamerican0792-66.
Pełny tekst źródłaRozprawy doktorskie na temat "Genetic algorithms"
Bland, Ian Michael. "Generic systolic arrays for genetic algorithms". Thesis, University of Reading, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312529.
Pełny tekst źródłaAguiar, Marilton Sanchotene de. "Análise formal da complexidade de algoritmos genéticos". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1998. http://hdl.handle.net/10183/25941.
Pełny tekst źródłaThe objective of the work is to study the viability of treating optimization problems, considered intractable, through Genetic Algorithms, developing approaches for the qualitative evaluation of a Genetic Algorithm. Inside this theme, approached areas: complexity, classes of problems, analysis and development of algorithms and Genetic Algorithms, this last one being central object of the study. As product of the study of this theme, a development method of Genetic Algorithms is proposed, using the whole formal study of types of problems, development of approximate algorithms and complexity analysis. The fact that a problem theoretically solvable isn’t enough to mean that it is solvable in pratice. A problem is denominated easy if in the worst case it possesses an algorithm reasonably efficient. And an algorithm is said reasonably efficient when a polynomial p exists such that for any entrance size n the algorithm terminates at maximum of p(n) steps [SZW 84]. Since a polynomial can be of very high order, then an algorithm of polynomial complexity can be very inefficient. The premise of the Genetic Algorithms is that one can find approximate solutions of problems of great computational complexity by means of a process of simulated evolution [LAG 96]. As product of the study of this theme, a method of development of Genetic Algorithms with the quality conscience is proposed, using the whole formal study of types of problems, development of approximate algorithms and complexity analysis. The axiom set has the purpose of giving the semantics of the algorithm, in other words, it defines formally the operation of the algorithm, more specifically of the functions and procedures of the algorithm. And this, facilitates the planner of algorithms a larger safety in the development, because in order to prove the correction of a Genetic Algorithm that satisfies that model it is only necessary to prove that the procedures satisfy the axioms. To have conscience of the quality of an approximate algorithm, two factors are important: the accuracy and the complexity. This work lifts the important points for the study of the complexity of a Genetic Algorithm. Unhappily, they are conflicting factors, because as larger the accuracy, worse (higher) it is the complexity, and vice-versa. Thus, a study of the quality of a Genetic Algorithm, considered an approximate algorithm, would be only complete with the consideration of these two factors. But, this work provides a great step in direction of the study of the viability of the treatment of optimization problems through Genetic Algorithms.
Abu-Bakar, Nordin. "Adaptive genetic algorithms". Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343268.
Pełny tekst źródłaHayes, Christina Savannah Maria. "Generic properties of the infinite population genetic algorithm". Diss., Montana State University, 2006. http://etd.lib.montana.edu/etd/2006/hayes/HayesC0806.pdf.
Pełny tekst źródłaWagner, Stefan. "Looking inside genetic algorithms /". Linz : Trauner, 2005. http://aleph.unisg.ch/hsgscan/hm00116856.pdf.
Pełny tekst źródłaCole, Rowena Marie. "Clustering with genetic algorithms". University of Western Australia. Dept. of Computer Science, 1998. http://theses.library.uwa.edu.au/adt-WU2003.0008.
Pełny tekst źródłaLapthorn, Barry Thomas. "Helioseismology and genetic algorithms". Thesis, Queen Mary, University of London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271261.
Pełny tekst źródłaDelman, Bethany. "Genetic algorithms in cryptography /". Link to online version, 2003. https://ritdml.rit.edu/dspace/handle/1850/263.
Pełny tekst źródłaKrüger, Franz David, i Mohamad Nabeel. "Hyperparameter Tuning Using Genetic Algorithms : A study of genetic algorithms impact and performance for optimization of ML algorithms". Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42404.
Pełny tekst źródłaAs machine learning (ML) is being more and more frequent in the business world, information gathering through Data mining (DM) is on the rise, and DM-practitioners are generally using several thumb rules to avoid having to spend a decent amount of time to tune the hyperparameters (parameters that control the learning process) of an ML algorithm to gain a high accuracy score. The proposal in this report is to conduct an approach that systematically optimizes the ML algorithms using genetic algorithms (GA) and to evaluate if and how the model should be constructed to find global solutions for a specific data set. By implementing a GA approach on two ML-algorithms, K-nearest neighbors, and Random Forest, on two numerical data sets, Iris data set and Wisconsin breast cancer data set, the model is evaluated by its accuracy scores as well as the computational time which then is compared towards a search method, specifically exhaustive search. The results have shown that it is assumed that GA works well in finding great accuracy scores in a reasonable amount of time. There are some limitations as the parameter’s significance towards an ML algorithm may vary.
Yan, Ping. "Theory of simple genetic algorithms". Thesis, University of Macau, 2000. http://umaclib3.umac.mo/record=b1446649.
Pełny tekst źródłaKsiążki na temat "Genetic algorithms"
Man, K. F., K. S. Tang i S. Kwong. Genetic Algorithms. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0577-0.
Pełny tekst źródłaAnup, Kumar, i Gupta Yash P, red. Genetic algorithms. Oxford: Pergamon, 1995.
Znajdź pełny tekst źródła1942-, Buckles Bill P., i Petry Fred, red. Genetic algorithms. Los Alamitos, Calif: IEEE Computer Society Press, 1986.
Znajdź pełny tekst źródłaLuque, Gabriel, i Enrique Alba. Parallel Genetic Algorithms. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22084-5.
Pełny tekst źródłaMutingi, Michael, i Charles Mbohwa. Grouping Genetic Algorithms. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-44394-2.
Pełny tekst źródłaHaupt, Randy L. Practical genetic algorithms. Wyd. 2. Hoboken, N.J: John Wiley, 2004.
Znajdź pełny tekst źródłaHaupt, Randy L. Practical genetic algorithms. New York: Wiley, 1998.
Znajdź pełny tekst źródłaDr, Herrera Francisco, i Verdegay José-Luis, red. Genetic algorithms and soft computing. Heidelberg: Physica-Verlag, 1996.
Znajdź pełny tekst źródłaLance, Chambers, red. The practical handbook of genetic algorithms: Applications. Wyd. 2. Boca Raton, Fla: Chapman & Hall/CRC, 2001.
Znajdź pełny tekst źródłaLance, Chambers, red. Practical handbook of genetic algorithms. Boca Raton: CRC Press, 1995.
Znajdź pełny tekst źródłaCzęści książek na temat "Genetic algorithms"
Hardy, Yorick, i Willi-Hans Steeb. "Genetic Algorithms". W Classical and Quantum Computing, 313–400. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8366-5_15.
Pełny tekst źródłaDu, Ke-Lin, i M. N. S. Swamy. "Genetic Algorithms". W Search and Optimization by Metaheuristics, 37–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41192-7_3.
Pełny tekst źródłaSastry, Kumara, David E. Goldberg i Graham Kendall. "Genetic Algorithms". W Search Methodologies, 93–117. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-6940-7_4.
Pełny tekst źródłaRathore, Heena. "Genetic Algorithms". W Mapping Biological Systems to Network Systems, 97–106. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29782-8_8.
Pełny tekst źródłaAnsari, Nirwan, i Edwin Hou. "Genetic Algorithms". W Computational Intelligence for Optimization, 83–97. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6331-0_6.
Pełny tekst źródłaRowe, Jonathan E. "Genetic Algorithms". W Springer Handbook of Computational Intelligence, 825–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-43505-2_42.
Pełny tekst źródłaReeves, Colin R. "Genetic Algorithms". W Handbook of Metaheuristics, 109–39. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1665-5_5.
Pełny tekst źródłaDracopoulos, Dimitris C. "Genetic Algorithms". W Perspectives in Neural Computing, 111–31. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0903-7_7.
Pełny tekst źródłaKingdon, Jason. "Genetic Algorithms". W Perspectives in Neural Computing, 55–80. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0949-5_4.
Pełny tekst źródłaDawid, Herbert. "Genetic Algorithms". W Lecture Notes in Economics and Mathematical Systems, 37–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-00211-7_3.
Pełny tekst źródłaStreszczenia konferencji na temat "Genetic algorithms"
Skomorokhov, Alexander O. "Genetic algorithms". W the conference. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/253341.253399.
Pełny tekst źródłaAlfonseca, Manuel. "Genetic algorithms". W the international conference. New York, New York, USA: ACM Press, 1991. http://dx.doi.org/10.1145/114054.114056.
Pełny tekst źródłaButt, Fouad, i Abdolreza Abhari. "Genetic algorithms". W the 2010 Spring Simulation Multiconference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878537.1878779.
Pełny tekst źródłaPandey, Hari Mohan, Anurag Dixit i Deepti Mehrotra. "Genetic algorithms". W the CUBE International Information Technology Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2381716.2381766.
Pełny tekst źródłaChapman, Colin D., Kazuhiro Saitou i Mark J. Jakiela. "Genetic Algorithms As an Approach to Configuration and Topology Design". W ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0338.
Pełny tekst źródłaJesus, Alexandre D., Arnaud Liefooghe, Bilel Derbel i Luís Paquete. "Algorithm selection of anytime algorithms". W GECCO '20: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3377930.3390185.
Pełny tekst źródłaCarlson, Susan E., Michael Ingrim i Ronald Shonkwiler. "Component Selection Using Genetic Algorithms". W ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0336.
Pełny tekst źródłaLadkany, George S., i Mohamed B. Trabia. "Incorporating Twinkling in Genetic Algorithms for Global Optimization". W ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49256.
Pełny tekst źródłaMisir, Mustafa, Stephanus Daniel Handoko i Hoong Chuin Lau. "Building algorithm portfolios for memetic algorithms". W GECCO '14: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2598394.2598455.
Pełny tekst źródłaAlba, Enrique. "Cellular genetic algorithms". W GECCO '14: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2598394.2605356.
Pełny tekst źródłaRaporty organizacyjne na temat "Genetic algorithms"
Arthur, Jennifer Ann. Genetic Algorithms. Office of Scientific and Technical Information (OSTI), sierpień 2017. http://dx.doi.org/10.2172/1375151.
Pełny tekst źródłaSharp, David H., John Reinitz i Eric Mjolsness. Genetic Algorithms for Genetic Neural Nets. Fort Belvoir, VA: Defense Technical Information Center, styczeń 1991. http://dx.doi.org/10.21236/ada256223.
Pełny tekst źródłaKargupta, H. Messy genetic algorithms: Recent developments. Office of Scientific and Technical Information (OSTI), wrzesień 1996. http://dx.doi.org/10.2172/378868.
Pełny tekst źródłaMessa, K., i M. Lybanon. Curve Fitting Using Genetic Algorithms. Fort Belvoir, VA: Defense Technical Information Center, październik 1991. http://dx.doi.org/10.21236/ada247206.
Pełny tekst źródłaThomas, E. V. Frequency selection using genetic algorithms. Office of Scientific and Technical Information (OSTI), maj 1993. http://dx.doi.org/10.2172/10177075.
Pełny tekst źródłaVlek, R. J., i D. J. M. Willems. Recipe reconstruction with genetic algorithms. Wageningen: Wageningen Food & Biobased Research, 2021. http://dx.doi.org/10.18174/540621.
Pełny tekst źródłaCobb, Helen G., i John J. Grefenstette. Genetic Algorithms for Tracking Changing Environments. Fort Belvoir, VA: Defense Technical Information Center, styczeń 1993. http://dx.doi.org/10.21236/ada294075.
Pełny tekst źródłaPittman, Jennifer, i C. A. Murthy. Optimal Line Fitting Using Genetic Algorithms. Fort Belvoir, VA: Defense Technical Information Center, lipiec 1997. http://dx.doi.org/10.21236/ada328266.
Pełny tekst źródłaGoldberg, David. Competent Probabilistic Model Building Genetic Algorithms. Fort Belvoir, VA: Defense Technical Information Center, lipiec 2003. http://dx.doi.org/10.21236/ada416564.
Pełny tekst źródłaVemuri, V. R. Genetic algorithms at UC Davis/LLNL. Office of Scientific and Technical Information (OSTI), grudzień 1993. http://dx.doi.org/10.2172/10122640.
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