Generating fuzzy rules by a GA-based method from input-output data

淡江大學機構典藏 > 工學院 > 電機工程學系暨研究所 > 會議論文 > Item 987654321/38699

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题名:	Generating fuzzy rules by a GA-based method from input-output data
其它题名:	從輸出入資料中建立模糊規則之以遺傳演算為基的方法
作者:	Wong, Ching-chang;Chen, Chia-chong
贡献者:	淡江大學電機工程學系
日期:	1999-10
上传时间:	2010-04-15 11:37:55 (UTC+8)
出版者:	Institute of Electrical and Electronics Engineers (IEEE)
摘要:	A method based on the concepts of the genetic algorithm (GA) and recursive least-squares method is proposed to construct a fuzzy system directly from some gathered input-output data of the discussed problem. The proposed method can find an appropriate fuzzy system with fewer rules to approach an identified system under the condition that the constructed fuzzy system must satisfy a predetermined acceptable performance. In this method, each individual in the GA is constructed to determine the number of fuzzy rules and the premise part of the fuzzy system, and the recursive least-squares method is used to determine the consequent part of the constructed fuzzy system described by this individual. Finally, two identification problems of nonlinear systems are utilized to illustrate the efficiency of the proposed method.
關聯:	Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on (Volume:5 ), pp.278-283
DOI:	10.1109/ICSMC.1999.815561
显示于类别:	[電機工程學系暨研究所] 會議論文

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