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Design of Interpretable Fuzzy Systems

  • Book
  • © 2017

Overview

Authors:
  1. Krzysztof Cpałka

    1. Czestochowa University of Technology, Institute of Computational Intelligence Czestochowa University of Technology, Częstochowa, Poland

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  • Presents insights into the design of interpretable fuzzy systems
  • Is intended primarily for researchers in fuzzy systems and computational intelligence
  • Written by a leading expert in the field
  • Includes supplementary material: sn.pub/extras

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

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xi
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  2. Introduction

    • Krzysztof Cpałka
    Pages 1-10

  3. Selected Topics in Fuzzy Systems Designing

    • Krzysztof Cpałka
    Pages 11-25

  4. Introduction to Fuzzy System Interpretability

    • Krzysztof Cpałka
    Pages 27-36

  5. Improving Fuzzy Systems Interpretability by Appropriate Selection of Their Structure

    • Krzysztof Cpałka
    Pages 37-60

  6. Interpretability of Fuzzy Systems Designed in the Process of Gradient Learning

    • Krzysztof Cpałka
    Pages 61-90

  7. Interpretability of Fuzzy Systems Designed in the Process of Evolutionary Learning

    • Krzysztof Cpałka
    Pages 91-130

  8. Case Study: Interpretability of Fuzzy Systems Applied to Nonlinear Modelling and Control

    • Krzysztof Cpałka
    Pages 131-162

  9. Case Study: Interpretability of Fuzzy Systems Applied to Identity Verification

    • Krzysztof Cpałka
    Pages 163-189

  10. Concluding Remarks and Future Perspectives

    • Krzysztof Cpałka
    Pages 191-193

  11. Back Matter

    Pages 195-196
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Keywords

About this book

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.

Authors and Affiliations

  • Czestochowa University of Technology, Institute of Computational Intelligence Czestochowa University of Technology, Częstochowa, Poland

    Krzysztof Cpałka

Bibliographic Information

  • Book Title: Design of Interpretable Fuzzy Systems

  • Authors: Krzysztof Cpałka

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-52881-6

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2017

  • Hardcover ISBN: 978-3-319-52880-9Published: 09 February 2017

  • Softcover ISBN: 978-3-319-85006-1Published: 04 May 2018

  • eBook ISBN: 978-3-319-52881-6Published: 31 January 2017

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XI, 196

  • Number of Illustrations: 65 b/w illustrations

  • Topics: Computational Intelligence, Artificial Intelligence

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