Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

  • Humberto Bustince
  • Francisco Herrera
  • Javier Montero

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 220)

Table of contents

  1. Front Matter
    Pages I-XX
  2. Foundations: Representation and Aggregation

    1. Front Matter
      Pages 1-1
    2. Simon Coupland, Robert John
      Pages 3-22
    3. Krassimir T. Atanassov
      Pages 23-43
    4. Eric C. C. Tsang, QingCai Chen, Suyun Zhao, Daniel S. Yeung, Xizhao Wang
      Pages 45-64
    5. Gleb Beliakov, Tomasa Calvo
      Pages 99-120
    6. Radko Mesiar, Anna Kolesárová, Tomasa Calvo, Magda Komorníková
      Pages 121-144
    7. Tomasa Calvo, Gleb Beliakov
      Pages 145-162
  3. From Decision Making to Data Mining, Web Intelligence and Computer Vision

    1. Front Matter
      Pages 205-205
    2. János Fodor, Bernard de Baets
      Pages 207-217
    3. Francisco Chiclana, Enrique Herrera-Viedma, Sergio Alonso, Ricardo Alberto, Marques Pereira
      Pages 219-237
    4. Salvatore Greco, Benedetto Matarazzo, Roman Słowiński
      Pages 239-261
    5. Bonifacio Llamazares, José Luis García-Lapresta
      Pages 297-315
    6. Luis Martínez, Luis G. Pérez, Jun Liu
      Pages 317-334

About this book

Introduction

This carefully edited book presents an up-to-date state of current research in the use of fuzzy sets and their extensions, paying attention to foundation issues and to their application to four important areas where fuzzy sets are seen to be an important tool for modelling and solving problems.

The book contains 34 chapters divided into two parts. The first part is divided into two sections. Section 1 contains four review papers introducing some non standard representations that extend fuzzy sets (type-2 fuzzy sets, Atanassov’s IFS, fuzzy rough sets and computing with words under the fuzzy sets perspective). Section 2 reviews different aggregation issues from a theoretical and practical point of view; this second part is divided into four sections. Section 3 is devoted to decision making, with seven papers that show how fuzzy sets and their extensions are an important tool for modelling choice problems. Section 4 includes eight papers that cover different aspects on the use of fuzzy sets and their extensions in data mining, giving an illustrative review of the state of the art on the topic. Section 5 is devoted to the emergent topic of web intelligence and contains four papers that show the use of fuzzy sets theory in some problems that can be tackled in this topic. Section 6 is devoted to the use of fuzzy sets and their extensions in the field of computer vision, suggesting how these can be an useful tool in this area.

This volume will be extremely useful to any non-expert reader who is keen to get a good overview on the latest developments in this research field. It will also support those specialists who wish to discover the latest results and trends in the abovementioned areas.

Keywords

Computer Vision Fuzziness Fuzzy Soft Computing algorithms data mining fuzzy logic fuzzy set image processing intelligent systems logic machine learning model modeling semantics

Editors and affiliations

  • Humberto Bustince
    • 1
  • Francisco Herrera
    • 2
  • Javier Montero
    • 3
  1. 1.Department of Automatics and ComputationUniversidad Pública de NavarraSpain
  2. 2.Department of Computer Science and Artificial Intelligence (DECSAI)University of GranadaPeriodista Daniel Saucedo Aranda s/nSpain
  3. 3.Faculty of MathematicsUniversidad Complutense28040 MadridSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-73723-0
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-73722-3
  • Online ISBN 978-3-540-73723-0
  • Series Print ISSN 1434-9922
  • About this book