Advances in Type-2 Fuzzy Sets and Systems

Theory and Applications

  • Alireza Sadeghian
  • Jerry M. Mendel
  • Hooman Tahayori

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 301)

Table of contents

  1. Front Matter
    Pages i-x
  2. Theoretical Foundations

    1. Front Matter
      Pages 1-1
    2. Juan Carlos Figueroa-García
      Pages 49-64
    3. Christian Wagner, Hani Hagras
      Pages 65-80
    4. Simon Coupland, Robert John
      Pages 81-96
    5. John Harding, Carol L. Walker, Elbert Walker
      Pages 97-112
    6. Janet Aisbett, John T. Rickard
      Pages 113-129
  3. Type-2 Fuzzy Set Membership Function Generation

    1. Front Matter
      Pages 131-131
    2. Masoomeh Moharrer, Hooman Tahayori, Alireza Sadeghian
      Pages 133-146
    3. Miguel Pagola, Edurne Barrenechea, Javier Fernández, Aranzazu Jurio, Mikel Galar, Jose Antonio Sanz et al.
      Pages 147-163
  4. Applications

    1. Front Matter
      Pages 185-185
    2. Patricia Melin, Oscar Castillo
      Pages 187-201
    3. Chang -Shing Lee, Mei -Hui Wang, Chin -Yuan Hsu, Zhi -Wei Chen
      Pages 237-256
  5. Back Matter
    Pages 257-262

About this book


This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet.  The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.


Computational Intelligence Fuzzy logic Fuzzy sets Granular Computing Soft Computing Type-2 Fuzzy Sets

Editors and affiliations

  • Alireza Sadeghian
    • 1
  • Jerry M. Mendel
    • 2
  • Hooman Tahayori
    • 3
  1. 1.Ryerson UniversityTorontoCanada
  2. 2.Hughes Aircraft Electrical Engineering B, Department of Electrical Engineering - SUniversity of Southern CaliforniaLos AngelesUSA
  3. 3.Ryerson UniversityTorontoCanada

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-1-4614-6665-9
  • Online ISBN 978-1-4614-6666-6
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site
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