Improvement of the cluster searching algorithm in Sugeno and Yasukawa's qualitative modeling approach

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Abstract

Fuzzy modeling has become very popular because of its main feature being the ability to assign meaningful linguistic labels to the fuzzy sets in the rule base. This paper examines Sugeno and Yasukawa's qualitative modeling approach, and addresses one of the remarks in the original paper. We propose a cluster search algorithm that can be used to provide a better projection of the output space to the input space. This algorithm can efficiently identify two or more fuzzy clusters in the input space that have the same output fuzzy cluster. © Springer-Verlag 2001.

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APA

Wong, K. W., Kóczy, L. T., Gedeon, T. D., Chong, A., & Tikk, D. (2001). Improvement of the cluster searching algorithm in Sugeno and Yasukawa’s qualitative modeling approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2206 LNCS, pp. 536–549). Springer Verlag. https://doi.org/10.1007/3-540-45493-4_54

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