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Design of Interpretable Fuzzy Systems

  • Krzysztof Cpałka

Part of the Studies in Computational Intelligence book series (SCI, volume 684)

About this book

Introduction

This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.

Keywords

Fuzzy Systems Interpretable Fuzzy Systems Design of Interpretable Fuzzy Systems Computational Intelligence Intelligent Systems

Authors and affiliations

  • Krzysztof Cpałka
    • 1
  1. 1.Czestochowa University of TechnologyInstitute of Computational Intelligence Czestochowa University of TechnologyCzęstochowaPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-52881-6
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-52880-9
  • Online ISBN 978-3-319-52881-6
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site