Real-coded Genetic Optimization of Fuzzy Clustering

Blekas, K; Stafylopatis, A

dc.contributor.author	Blekas, K	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:48:23Z
dc.date.available	2014-03-01T02:48:23Z
dc.date.issued	1996	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33777
dc.subject	Fuzzy C Means Algorithm	en
dc.subject	Fuzzy C Means Clustering	en
dc.subject	Fuzzy Clustering	en
dc.subject	Genetics	en
dc.title	Real-coded Genetic Optimization of Fuzzy Clustering	en
heal.type	conferenceItem	en
heal.publicationDate	1996	en
heal.abstract	: A genetic approach is developed, which is suitable for the optimization of fuzzy c-means clustering.The approach is based on real encoding of the prototype variables (cluster centers) and uses appropriate geneticoperators and techniques to optimize the clustering criterion. Experimental results concerning difficult clusteringproblems show that the proposed approach is very successful in generating fuzzy partitions and prototypes andoutperforms the	en
heal.journalName	European Congress on Intelligent Techniques and Soft Computing - link	en