Adjust genetic algorithm parameter by fuzzy system

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Auteur principal: Tayebe Noshadi
Format: Artículo científico
Langue:en
Publié: Universidade Federal de Santa Maria 2015
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author Tayebe Noshadi
author_facet Tayebe Noshadi
contents Adjust genetic algorithm parameter by fuzzy system Tayebe Noshadi Marzieh Dadvar Nastaran Mirza Shima Shamseddini Estudios Ambientales parallel fuzzy systems Genetic algorithms genetic algorithms parallel genetic algorithm immigration Genetic algorithm is one of the random search es algorithm . Genetic algorithm is a method that uses genetic evolution as a model of problem solving. Genetic algorithm for selecting the best population, but the choices are not a s heuristic information to be used in specific issues. In order to obtain optimal soluti ons and efficient use of fuzzy systems with heuristic rules that we would aim to increase the efficiency of parallel genetic algorithms using fuzzy logic immigration, which in fact do this by optimizing the paramete rs compared with the use of fuzzy system is done. 2015 artículo científico 0100-8307 https://www.redalyc.org/articulo.oa?id=467547683025 en http://www.redalyc.org/revista.oa?id=4675 Ciência e Natura application/pdf Universidade Federal de Santa Maria Ciência e Natura (Brasil) Num.6-2 Vol.37
format Artículo científico
id redalyc_467547683025
institution Redalyc
language en
publishDate 2015
publisher Universidade Federal de Santa Maria
spellingShingle Adjust genetic algorithm parameter by fuzzy system
Tayebe Noshadi
Estudios Ambientales
parallel
fuzzy systems
Genetic algorithms
genetic algorithms
parallel genetic algorithm immigration
Adjust genetic algorithm parameter by fuzzy system Tayebe Noshadi Marzieh Dadvar Nastaran Mirza Shima Shamseddini Estudios Ambientales parallel fuzzy systems Genetic algorithms genetic algorithms parallel genetic algorithm immigration Genetic algorithm is one of the random search es algorithm . Genetic algorithm is a method that uses genetic evolution as a model of problem solving. Genetic algorithm for selecting the best population, but the choices are not a s heuristic information to be used in specific issues. In order to obtain optimal soluti ons and efficient use of fuzzy systems with heuristic rules that we would aim to increase the efficiency of parallel genetic algorithms using fuzzy logic immigration, which in fact do this by optimizing the paramete rs compared with the use of fuzzy system is done. 2015 artículo científico 0100-8307 https://www.redalyc.org/articulo.oa?id=467547683025 en http://www.redalyc.org/revista.oa?id=4675 Ciência e Natura application/pdf Universidade Federal de Santa Maria Ciência e Natura (Brasil) Num.6-2 Vol.37
title Adjust genetic algorithm parameter by fuzzy system
topic Estudios Ambientales
parallel
fuzzy systems
Genetic algorithms
genetic algorithms
parallel genetic algorithm immigration
url https://www.redalyc.org/articulo.oa?id=467547683025