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Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision

  • Book
  • © 2008

Overview

  • Recent advances of fuzzy sets and their extensions
  • Special focus on fuzzy logic foundations (representation and aggregation) and computer vision applications, decision making, web intelligence and data mining

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

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Table of contents (34 chapters)

  1. Foundations: Representation and Aggregation

  2. From Decision Making to Data Mining, Web Intelligence and Computer Vision

Keywords

About this book

Fuzzy Sets and Their Extensions: Representation, Aggregation and Models Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision Fuzzy sets are now more than 40 years old, and have come of age. However, the development of fuzzy set theory at the theoretical level, and its successful appli- tions to science and technology have often run in isolation. Only a little part of the theoretical apparatus was effectively used in past applications. The most prominent ones, namely fuzzy rule-based modeling and control engineering, were directly - spired from a seminal paper by Lot? Zadeh in 1973, suggesting how to use expert knowledge for synthetizing control laws, and from the ?rst experiments published by Abe Mamdani. Later in the eighties, when spectacular applications were bl- soming in Japan, fuzzy rule-based systems were systematized and simpli?ed by Michio Sugeno and colleagues, and became a basic approach to non-linear system modeling and control, soon hybridized with neural networks in the nineties. Thus fuzzy systems signi?cantly contributed to the raise of computational intelligence, and a lot of learning techniques for the construction of (supposedly interpretable) fuzzy models from data were developed under the ?ag of soft computing. Even if this area was quite successful, it is patent that the role, in the success of fuzzy logic, of new fuzzy set-related concepts developed quite at the same time in themathematicalnicheofthefuzzyset communitywaslimited.

Editors and Affiliations

  • Department of Automatics and Computation, Universidad Pública de Navarra, Spain

    Humberto Bustince

  • Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada, Periodista Daniel Saucedo Aranda s/n, Spain

    Francisco Herrera

  • Faculty of Mathematics, Universidad Complutense, 28040 Madrid, Spain

    Javier Montero

Bibliographic Information

  • Book Title: Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

  • Book Subtitle: Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision

  • Editors: Humberto Bustince, Francisco Herrera, Javier Montero

  • Series Title: Studies in Fuzziness and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-540-73723-0

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2008

  • Hardcover ISBN: 978-3-540-73722-3Published: 25 October 2007

  • Softcover ISBN: 978-3-642-09290-9Published: 22 November 2010

  • eBook ISBN: 978-3-540-73723-0Published: 30 October 2007

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: XX, 674

  • Topics: Theory of Computation, Mathematical and Computational Engineering, Artificial Intelligence

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