Evolutionarily adjusting membership functions in Takagi-Sugeno fuzzy systems
學年 99
學期 2
出版(發表)日期 2011-05-01
作品名稱 Evolutionarily adjusting membership functions in Takagi-Sugeno fuzzy systems
作品名稱(其他語言)
著者 Hong, Tzung-Pei; Lin, Wei-Tee; Chen, Chun-Hao; Ouyang, Chen-Sen
單位 淡江大學資訊工程學系
出版者 Olney: Inderscience Publishers
著錄名稱、卷期、頁數 International Journal of Intelligent Information and Database Systems 5(3), pp.229–245
摘要 Fuzzy set theory has been used more and more frequently in intelligent systems because of its simplicity and similarity to human reasoning. It usually uses a fuzzy inference system to handle new cases for making decisions or controlling actions. In the past, Takagi and Sugeno proposed a well-known fuzzy model, namely TS fuzzy model, to improve the precision of inference results. In this paper, we try to automatically adjust the membership functions appropriate for the TS fuzzy model. A GA-based learning algorithm is thus proposed to achieve the purpose. The proposed approach considers the shapes of membership functions in fitness evaluation in addition to the accuracy. The experimental results show that the proposed approach can derive the membership functions in the Takagi-Sugeno system with low errors and good shapes.
關鍵字
語言 en
ISSN 1751-5858
期刊性質 國外
收錄於 EI
產學合作
通訊作者 Hong, Tzung-Pei
審稿制度
國別 GBR
公開徵稿
出版型式 紙本
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