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Complexity Management in Fuzzy Systems

A Rule Base Compression Approach

  • Alexander Gegov

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 211)

Table of contents

  1. Front Matter
    Pages I-XV
  2. Alexander Gegov
    Pages 1-6
  3. Alexander Gegov
    Pages 7-16
  4. Alexander Gegov
    Pages 17-31
  5. Alexander Gegov
    Pages 115-151
  6. Alexander Gegov
    Pages 185-268
  7. Alexander Gegov
    Pages 341-344
  8. Back Matter
    Pages 345-351

About this book

Introduction

This book presents a systematic study on the inherent complexity in fuzzy systems, resulting from the large number and the poor transparency of the fuzzy rules. The study uses a novel approach for complexity management, aimed at compressing the fuzzy rule base by removing the redundancy while preserving the solution. The compression is based on formal methods for presentation, manipulation, transformation and simplification of fuzzy rule bases, which are illustrated by algorithms as well as results from numerous examples and two case studies. The results are directly applicable or easily extendable to a wide class of fuzzy systems and detailed benchmarks for expanding these systems to new areas such as fuzzy networks and fuzzy multi-agent systems are introduced. The intended readers are people from both academia and industry, who would be interested in building and implementing advanced fuzzy systems.

Keywords

Complex fuzzy systems Computer-Aided Design (CAD) Fuzzy Fuzzy rule aggregation Fuzzy rule base compression Fuzzy rule base reduction Fuzzy rule filtration Transformation algorithm algorithms complexity formal method fuzzy system fuzzy systems multi-agent system

Authors and affiliations

  • Alexander Gegov
    • 1
  1. 1.School of Computing Buckingham BuildingUniversity of PortsmouthPortsmouthUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-38885-2
  • Copyright Information Springer 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-38883-8
  • Online ISBN 978-3-540-38885-2
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site