Generating fuzzy rules by a GA-based method from input-output data
學年 88
學期 1
發表日期 1999-10-01
作品名稱 Generating fuzzy rules by a GA-based method from input-output data
作品名稱(其他語言) 從輸出入資料中建立模糊規則之以遺傳演算為基的方法
著者 Wong, Ching-chang; Chen, Chia-chong
作品所屬單位 淡江大學電機工程學系
出版者 Institute of Electrical and Electronics Engineers (IEEE)
會議名稱 Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
會議地點 Tokyo, Japan
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.
關鍵字
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間
通訊作者
國別 JPN
公開徵稿 Y
出版型式 紙本
出處 Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on (Volume:5 ), pp.278-283
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/38699 )

機構典藏連結