International Journal of Fuzzy Logic and Intelligent Systems

  • 제5권2호
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  • Pages.95-101
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  • 2005
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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A New Learning Algorithm of Neuro-Fuzzy Modeling Using Self-Constructed Clustering

  • Ryu, Jeong-Woong (School of Electrical & Computer Engineering, Chungbuk National University) ;
  • Song, Chang-Kyu (School of Electrical & Computer Engineering, Chungbuk National University) ;
  • Kim, Sung-Suk (School of Electrical & Computer Engineering, Chungbuk National University) ;
  • Kim, Sung-Soo (School of Electrical & Computer Engineering, Chungbuk National University)
  • 발행 : 2005.06.01
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초록

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

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참고문헌

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