An enhanced approach to rule base simplification of first-order takagi-sugeno fuzzy inference systems

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Abstract

Fuzzy rule base simplification is used to reduce the complexity of fuzzy models identified from the data. In this paper, an enhanced approach is proposed for simplifying the rule base of fuzzy inference systems when all the membership functions for a variable are highly similar to one another. In this case it is possible to remove a variable from the rule antecedent, but keep it in the rule consequent. Experimental results show that simpler rules can be obtained while barely sacrificing accuracy.

Original languageEnglish
Title of host publicationAdvances in Fuzzy Logic and Technology 2017
Subtitle of host publicationProceedings of: EUSFLAT- 2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, September 11-15, 2017, Warsaw, Poland IWIFSGN’2017 – The Sixteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, September 13-15, 2017, Warsaw, Poland
EditorsJ. Kacprzyk , E. Szmidt , S. Zadrożny , K.T. Atanassov, M. Krawczak
Place of PublicationDordrecht
PublisherSpringer
Pages92-103
Number of pages12
Volume2
ISBN (Electronic)978-3-319-66824-6
ISBN (Print)978-3-319-66823-9
DOIs
Publication statusPublished - 2018
Event4th Annual Symposium on Combinatorial Pattern Matching (CPM1993), June 2-4, 1993, Padova, Italy - Padova, Italy
Duration: 2 Jun 19934 Jun 1993

Publication series

NameAdvances in Intelligent Systems and Computing
Volume642
ISSN (Print)2194-5357

Conference

Conference4th Annual Symposium on Combinatorial Pattern Matching (CPM1993), June 2-4, 1993, Padova, Italy
Abbreviated titleCPM 1993
CountryItaly
CityPadova
Period2/06/934/06/93

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Keywords

  • Jaccard similarity merging
  • Rule base simplification
  • Takagi-Sugeno fuzzy inference systems
  • Transparent models

Cite this

Fuchs, C. E. M., Wilbik, A. M., van Loon, S. L. M., Boer, A-K., & Kaymak, U. (2018). An enhanced approach to rule base simplification of first-order takagi-sugeno fuzzy inference systems. In J. Kacprzyk , E. Szmidt , S. Zadrożny , K. T. Atanassov, & M. Krawczak (Eds.), Advances in Fuzzy Logic and Technology 2017: Proceedings of: EUSFLAT- 2017 – The 10th Conference of the European Society for Fuzzy Logic and Technology, September 11-15, 2017, Warsaw, Poland IWIFSGN’2017 – The Sixteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, September 13-15, 2017, Warsaw, Poland (Vol. 2, pp. 92-103). (Advances in Intelligent Systems and Computing; Vol. 642). Dordrecht: Springer. https://doi.org/10.1007/978-3-319-66824-6_9