Rule-base Self-extraction and Simplification for Fuzzy Systems

Guo Haixiang1、 Liu Tao2、 Zhu Kejun1

Strategic Study of CAE ›› 2004, Vol. 6 ›› Issue (10) : 52-58.

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PDF(3765 KB)
Strategic Study of CAE ›› 2004, Vol. 6 ›› Issue (10) : 52-58.
Academic Papers

Rule-base Self-extraction and Simplification for Fuzzy Systems

  • Guo Haixiang1、 Liu Tao2、 Zhu Kejun1

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Abstract

In this paper, a fuzzy model algorithm for a rule-base self-extraction and simplification is introduced. The method consistes of three steps: The first step is to classify the out-in space by constructing a fuzzy partition validity index, then the optimal number of dusters and, hence, the optimal number of rules are obtained; The second step is to construct the initial fuzzy system based on the optimal number of rules and neural networks; The third step is to get the function of computing similarity of fuzzy sets by fuzzy similarity analysis method. The similar fuzzy sets are merged to create a common fuzzy set in rule base based on threshold value. Thus a fuzzy system with interpretability and simplicity is obtained. At last, the fuzzy rules of productivity factor of China is extracted by the fuzzy system.

Keywords

similarity measures / fuzzy model / fuzzy rules / fuzzy sets

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Guo Haixiang,Liu Tao,Zhu Kejun. Rule-base Self-extraction and Simplification for Fuzzy Systems. Strategic Study of CAE, 2004, 6(10): 52‒58
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