Comments on "Constraining the optimization of a fuzzy logic controller"

doi:10.1109/3477.938270

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DC 欄位	值	語言
dc.contributor.author	Wu, MD	en_US
dc.contributor.author	Sun, CT	en_US
dc.date.accessioned	2014-12-08T15:43:35Z	-
dc.date.available	2014-12-08T15:43:35Z	-
dc.date.issued	2001-08-01	en_US
dc.identifier.issn	1083-4419	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/3477.938270	en_US
dc.identifier.uri	http://hdl.handle.net/11536/29473	-
dc.description.abstract	Genetic algorithms (GAs) are a highly effective and efficient means of solving optimization problems. Gene encoding, fitness landscape and genetic operations are vital to successfully developing a GA. Cheong and Lai(1) described a novel method, which employed an enhanced genetic algorithm with multiple populations, to optimize a fuzzy controller, and the experimental results revealed that their method was effective in producing a well-formed fuzzy rule-base. However, their encoding method and fitness function appear unnatural and inefficient. This study proposes an alternative method of concise genetic encoding and fitness design.	en_US
dc.language.iso	en_US	en_US
dc.subject	fuzzy modeling	en_US
dc.subject	genetic algorithms	en_US
dc.subject	polyploidy	en_US
dc.title	Comments on "Constraining the optimization of a fuzzy logic controller"	en_US
dc.type	Article	en_US
dc.identifier.doi	10.1109/3477.938270	en_US
dc.identifier.journal	IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS	en_US
dc.citation.volume	31	en_US
dc.citation.issue	4	en_US
dc.citation.spage	663	en_US
dc.citation.epage	666	en_US
dc.contributor.department	資訊工程學系	zh_TW
dc.contributor.department	Department of Computer Science	en_US
dc.identifier.wosnumber	WOS:000170320400017	-
dc.citation.woscount	0	-
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