Design of fuzzy classification system using genetic algorithms

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Title:	Design of fuzzy classification system using genetic algorithms
Authors:	Wong, Ching-chang;Chen, Chia-chong;Lin, Bo-chen
Contributors:	淡江大學電機工程學系
Date:	2000-05-07
Issue Date:	2010-04-15 11:37:20 (UTC+8)
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Abstract:	This paper proposes a GA-based method to construct an appropriate fuzzy classification system to maximize the number of correctly classified patterns and minimize the number of fuzzy rules. In this method, a fuzzy classification system is coded as an individual in the GA. A fitness function is defined such that it can guide the search procedure to select an appropriate fuzzy classification system to maximize the number of correctly classified patterns and minimize the number of fuzzy rules. Finally, a two-class classification problem is utilized to illustrate the efficiency of the proposed method
Relation:	Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on vol.1, pp.297-301
DOI:	10.1109/FUZZY.2000.838675
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Proceeding

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