A GA-based method for constructing fuzzy systems directly from numerical data
學年 89
學期 1
出版(發表)日期 2000-12-01
作品名稱 A GA-based method for constructing fuzzy systems directly from numerical data
作品名稱(其他語言)
著者 翁慶昌; Wong, Ching-chang; Chen, Chia-chong
單位 淡江大學電機工程學系
出版者 Piscataway: Institute of Electrical and Electronics Engineers (IEEE)
著錄名稱、卷期、頁數 IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 30(6), pp.904-911
摘要 A method based on the concepts of 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 a low number of 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 population 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, three identification problems of nonlinear systems are utilized to illustrate the effectiveness of the proposed method.
關鍵字
語言 en
ISSN 1083-4419
期刊性質
收錄於 SCI EI
產學合作
通訊作者
審稿制度
國別 USA
公開徵稿
出版型式
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46250 )

機構典藏連結