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Neuro-Fuzzy Architectures and Hybrid Learning

  • Danuta¬†Rutkowska

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 85)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Danuta Rutkowska
    Pages 1-3
  3. Danuta Rutkowska
    Pages 5-67
  4. Danuta Rutkowska
    Pages 69-103
  5. Danuta Rutkowska
    Pages 165-207
  6. Danuta Rutkowska
    Pages 209-228
  7. Danuta Rutkowska
    Pages 229-231
  8. Back Matter
    Pages 233-288

About this book

Introduction

The main idea of this book is to present novel connectionist architectures of neuro-fuzzy systems, especially those based on the logical approach to fuzzy inference. In addition, hybrid learning methods are proposed to train the networks. The neuro-fuzzy architectures plus hybrid learning are considered as intelligent systems within the framework of computational and artificial intelligence. The book also provides an overview of fuzzy sets and systems, neural networks, learning algorithms (including genetic algorithms and clustering methods), as well as expert systems and perception-based systems which incorporates computing with words.

Keywords

Artificial Intelligence Fuzzy Fuzzy Systems Learning Algorithms Neural Networks Neuro-Fuzzy Systems algorithms expert system fuzzy set fuzzy system genetic algorithms intelligence intelligent systems learning

Authors and affiliations

  • Danuta¬†Rutkowska
    • 1
  1. 1.Department of Computer EngineeringTechnical University of CzestochowaCzestochowaPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-7908-1802-4
  • Copyright Information Physica-Verlag Heidelberg 2002
  • Publisher Name Physica, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-7908-2500-8
  • Online ISBN 978-3-7908-1802-4
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site