Titlebook: Explainable Uncertain Rule-Based Fuzzy Systems; Jerry M. Mendel Textbook 2024Latest edition The Editor(s) (if applicable) and The Author(s

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Interval Type-2 Fuzzy Systems: Design Methods and Case Studies,ence system—ANFIS, and structure identification and feature extraction—SIFE—for TSK systems); and the continuation of the Chap. . five case studies from T1 to IT2 fuzzy systems (forecasting of time series, knowledge mining using surveys, rule-based classification of video traffic, fuzzy logic contro

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General Type-2 Fuzzy Systems,sign method and one extensive case study. Not only are derivations provided, but a lot of emphasis is also placed on understanding the potential benefits of using a WH GT2 fuzzy system over an IT2 fuzzy system..The coverage of this chapter focuses on singleton fuzzification, the use of the horizonta

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Aysen Bakioglu,Ozge Hacifazlioglumalized TSK); a comprehensive numerical example that illustrates all of the computations for one kind of a Mamdani fuzzy system and two kinds of TSK fuzzy systems (this example is continued in later chapters); fuzzy basis functions that provide a mathematical description of a fuzzy system from its i

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Sub-Surface Microstructural Analysisusing surveys, rule-based classification of video traffic, fuzzy logic control, and explainable type-1 fuzzy systems), all of which are re-examined in Chap. .. There are two appendixes: Appendix 1 introduces novel Constraints Almost Always Satisfied Parameters (CAASPs) for type-1 fuzzy sets and syst

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Techniques for Histopathological Analysis, 1 provides proofs for 10 theorems; Appendix 2 is about the properties of T2 FSs; Appendix 3 derives the union, intersection, and complement of IT2 FSs using type-1 fuzzy set mathematics; and, Appendix 4 is about cardinality and similarity of T2 FSs. 22 examples are used to illustrate the chapter’s

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H. N. Pollack,J. H. Sass,D. Stromeyerngleton, type-1 non-singleton, and IT2 non-singleton); (derivation of) input–output formulas for the fuzzy inference engine (also valid for GT2 fuzzy systems); the effects of the three kinds of fuzzifiers on the input–output formulas (valid for IT2 fuzzy systems); combining or not combining fired-ru