An Enhanced Approach to Rule Base Simplification of First-Order Takagi-Sugeno Fuzzy Inference Systems

Caro Fuchs; Anna Wilbik; Saskia van Loon; Arjen-Kars Boer; Uzay Kaymak

doi:10.1007/978-3-319-66824-6_9

An Enhanced Approach to Rule Base Simplification of First-Order Takagi-Sugeno Fuzzy Inference Systems

Caro Fuchs^*, Anna Wilbik, Saskia van Loon, Arjen-Kars Boer, Uzay Kaymak

^*Corresponding author for this work

Research output: Contribution to conference › Paper › Academic

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 language	English
Pages	92-103
DOIs	https://doi.org/10.1007/978-3-319-66824-6_9
Publication status	Published - 2017
Externally published	Yes
Event	Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets - Warsaw, Poland Duration: 11 Sept 2017 → 15 Sept 2017

Conference

Conference	Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets
Abbreviated title	EUSFLAT 2017, IWIFSGN 2017
Country/Territory	Poland
City	Warsaw
Period	11/09/17 → 15/09/17

Access to Document

10.1007/978-3-319-66824-6_9

Cite this

Fuchs, C., Wilbik, A., Loon, S. V., Boer, A.-K., & Kaymak, U. (2017). An Enhanced Approach to Rule Base Simplification of First-Order Takagi-Sugeno Fuzzy Inference Systems. 92-103. Paper presented at Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, Warsaw, Poland. https://doi.org/10.1007/978-3-319-66824-6_9

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author = "Caro Fuchs and Anna Wilbik and Loon, {Saskia van} and Arjen-Kars Boer and Uzay Kaymak",

note = "DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, EUSFLAT 2017, IWIFSGN 2017 ; Conference date: 11-09-2017 Through 15-09-2017",

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Fuchs, C, Wilbik, A, Loon, SV, Boer, A-K & Kaymak, U 2017, 'An Enhanced Approach to Rule Base Simplification of First-Order Takagi-Sugeno Fuzzy Inference Systems', Paper presented at Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, Warsaw, Poland, 11/09/17 - 15/09/17 pp. 92-103. https://doi.org/10.1007/978-3-319-66824-6_9

An Enhanced Approach to Rule Base Simplification of First-Order Takagi-Sugeno Fuzzy Inference Systems. / Fuchs, Caro; Wilbik, Anna; Loon, Saskia van et al.
2017. 92-103 Paper presented at Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, Warsaw, Poland.

Research output: Contribution to conference › Paper › Academic

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T1 - An Enhanced Approach to Rule Base Simplification of First-Order Takagi-Sugeno Fuzzy Inference Systems

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AU - Wilbik, Anna

AU - Loon, Saskia van

AU - Boer, Arjen-Kars

AU - Kaymak, Uzay

N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2017

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AB - 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.

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DO - 10.1007/978-3-319-66824-6_9

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T2 - Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets

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Fuchs C, Wilbik A, Loon SV, Boer AK, Kaymak U. An Enhanced Approach to Rule Base Simplification of First-Order Takagi-Sugeno Fuzzy Inference Systems. 2017. Paper presented at Proceedings of the Conference of the European Society for Fuzzy Logic and Technology, International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, Warsaw, Poland. doi: 10.1007/978-3-319-66824-6_9