A review of developments in fuzzy system models: Fuzzy rule bases to fuzzy functions | Zendy

İ.B. Türkşen | Zendy

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A review of developments in fuzzy system models: Fuzzy rule bases to fuzzy functions

Author(s) -

İ.B. Türkşen

Publication year - 2011

Publication title -

scientia iranica

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.299

H-Index - 51

eISSN - 2345-3605

pISSN - 1026-3098

DOI - 10.1016/j.scient.2011.04.001

Subject(s) - fuzzy logic , fuzzy set operations , fuzzy rule , context (archaeology) , defuzzification , fuzzy classification , variety (cybernetics) , computer science , mathematics , fuzzy mathematics , fuzzy set , artificial intelligence , data mining , fuzzy number , machine learning , geography , archaeology

In a historical context, we first review the development of fuzzy system models from “Fuzzy Rule Bases” proposed by Zadeh (1975) [1], with versions of Sugeno–Yasukawa (1993) [2] and Tagaki–Sugeno (1985) [3]. Secondly, we review the development of the “Fuzzy C-Regression Model” (FCRM), proposed by Hathaway and Bezdek (1993) [4], as well as “Combined FCM, and FCRM Algorithms, proposed by Höppner and Klawonn (2003) [5]. Thirdly, we review “Fuzzy Functions”, proposed by Türkşen (2008) [6] and further developed by Celikyilmaz and Türkşen (2008–2009) [7–9] in a variety of versions. An experimental assessment of various models are discussed in this writing

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