Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the ranking values of fuzzy sets |
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| Authors: | Li-Wei Lee Shyi-Ming Chen |
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| Affiliation: | aDepartment of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;bDepartment of Computer Science and Information Engineering, Jinwen University of Science and Technology, Taipei, Taiwan, ROC |
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| Abstract: | Fuzzy interpolative reasoning is an important research topic of sparse fuzzy rule-based systems. In recent years, some methods have been presented for dealing with fuzzy interpolative reasoning. However, the involving fuzzy sets appearing in the antecedents of fuzzy rules of the existing fuzzy interpolative reasoning methods must be normal and non-overlapping. Moreover, the reasoning conclusions of the existing fuzzy interpolative reasoning methods sometimes become abnormal fuzzy sets. In this paper, in order to overcome the drawbacks of the existing fuzzy interpolative reasoning methods, we present a new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on the ranking values of fuzzy sets. The proposed fuzzy interpolative reasoning method can handle the situation of non-normal and overlapping fuzzy sets appearing in the antecedents of fuzzy rules. It can overcome the drawbacks of the existing fuzzy interpolative reasoning methods in sparse fuzzy rule-based systems. |
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| Keywords: | Fuzzy interpolative reasoning Ranking values Ranking proportional interpolative coefficients Sparse fuzzy rule-based systems |
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