Genetic Algorithm-Based Fuzzy System Design Using a New Representation Scheme

Tzafestas, G; Raptis, N; Pimenides, T

dc.contributor.author	Tzafestas, G	en
dc.contributor.author	Raptis, N	en
dc.contributor.author	Pimenides, T	en
dc.date.accessioned	2014-03-01T01:52:40Z
dc.date.available	2014-03-01T01:52:40Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/26684
dc.relation.uri	http://www.ici.ro/eng/SIC/sic2003_2/art2.pdf	en
dc.subject	Fuzzy System	en
dc.subject	Genetic Algorithm	en
dc.subject	Level Set	en
dc.subject	Point of View	en
dc.subject	Problem Solving	en
dc.subject	Stochastic Search	en
dc.title	Genetic Algorithm-Based Fuzzy System Design Using a New Representation Scheme	en
heal.type	journalArticle	en
heal.publicationDate	2003	en
heal.abstract	Abstracts: Genetic algorithms (GA’s) are powerful stochastic search algorithms for general problem solving. Their effectiveness asa,tool for evolving ,other systems has ,been early identified and has gained increasing research interest. Fuzzy systems may stronglybenefit fromGA’ ssince theyinvolve a quite large number of parametersthat needto be tuned forth e systemto achieve the required performance. Such parameters include (but are not limited	en