Explainable Uncertain Rule-Based Fuzzy Systems by Jerry M. Mendel Paperback Book

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Explainable Uncertain Rule-Based Fuzzy Systems by Jerry M. Mendel

The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty — i.e., "type-2" fuzzy sets and systems.

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The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty — i.e., "type-2" fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications, from time-series forecasting to knowledge mining to classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.

Table of Contents

Introduction.- Part 1: Type-1 Fuzzy Sets and Systems.- Short Primers on Type-1Fuzzy SetsandFuzzy Logic.-Type-1Fuzzy LogicSystems.-Part2:Type-2Fuzzy Sets.- Sources of Uncertainty.-Type-2Fuzzy Sets.- OperationsonandProperties OFType-2Fuzzy Sets.-Type-2 RelationsandCompositions.- Centroid of aType-2Fuzzy Set:Type-Reduction.-Part3:Type-2Fuzzy LogicSystems.- Mamdani IntervalType-2Fuzzy LogicSystems(IT2 FLSS).- TSK IntervalType-2Fuzzy LogicSystems.- GeneralType-2Fuzzy LogicSystems(GT2 FLSS).- Conclusion.

Review

"Explainable uncertain rule-based fuzzy systems is a significant contribution to the field of computational intelligence. It provides valuable insights into the integration of uncertainty and interpretability in fuzzy logic systems, making it an essential resource for researchers and practitioners seeking to advance their understanding of explainable AI(XAI)." (Wael Badawy, Computing Reviews, June 27, 2025)

Details ISBN3031353803 Author Jerry M. Mendel Pages 580 Publisher Springer International Publishing AG Edition Description Third Edition 2024 Year 2025 ISBN-13 9783031353802 Format Paperback Imprint Springer International Publishing AG Place of Publication Cham Country of Publication Switzerland Alternative 9783031353772 DEWEY 511.313 Publication Date 2025-04-02 Country of Origin NL Product Class Description Computing: Professional & Programming ISBN-10 3031353803 UK Release Date 2025-04-02 Illustrations 231 Illustrations, color; 26 Illustrations, black and white Audience Educational: Primary & Secondary
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