제어로봇시스템학회:학술대회논문집
- 2002.10a
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- Pages.109.6-109
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- 2002
Fuzzy system construction based on Genetic Algorithms and fuzzy clustering
- Kwak, Keun-Chang (Chungbuk Nat'1 Univ.) ;
- Kim, Seoung-Suk (Chungbuk Nat'1 Univ.) ;
- Ryu, Jeong-Woong (Chungbuk Nat'1 Univ.) ;
- Chun, Myung-Geun (Chungbuk Nat'1 Univ.)
- Published : 2002.10.01
Abstract
In this paper, the scheme of fuzzy system construction using GA(genetic algorithm) and FCM(Fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. in the structure identification, input data is trans-formed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, the number of fuzzy rule is obtained by a given performance criterion. In the parameter identification, the premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this, one can systematically obtain optimal parameter and the v..
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