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http://dx.doi.org/10.5391/JKIIS.2002.12.4.334

Self-Organizing Fuzzy Modeling Using Creation of Clusters  

Koh, Taek-Beom (경주대학교 컴퓨터전자공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.12, no.4, 2002 , pp. 334-340 More about this Journal
Abstract
This paper proposes a self-organizing fuzzy modeling which can create a new hyperplane-shaped cluster by applying multiple regression to input/output data with relatively large fuzzy entropy, add the new cluster to fuzzy rule base and adjust parameters of the fuzzy model in repetition. Tn the coarse tuning, weighted recursive least squared algorithm and fuzzy C-regression model clustering are used and in the fine tuning, gradient descent algorithm is used to adjust parameters of the fuzzy model precisely And learning rates are optimized by utilizing meiosis-genetic algorithm. To check the effectiveness and feasibility of the suggested algorithm, four representative examples for system identification are examined and the performance of the identified fuzzy model is demonstrated in comparison with that of the conventional fuzzy models.
Keywords
자기구성 퍼지 모델링;클러스터 생성;퍼지 엔트로피;파라미터 동조;감수분열 유전알고리즘;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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