© 2011

Granular Computing and Intelligent Systems

Design with Information Granules of Higher Order and Higher Type

  • Witold Pedrycz
  • Shyi-Ming Chen


  • Self-contained book including all necessary prerequisites for working with granular computing and intelligent systems

  • Presents step-by-step explanations of more advanced concepts supported by a significant amount of illustrative numeric material

  • Written by leading experts in the field


Part of the Intelligent Systems Reference Library book series (ISRL, volume 13)

Table of contents

  1. Front Matter
  2. Andrzej Skowron, Jarosław Stepaniuk, Roman Swiniarski
    Pages 35-55
  3. Alfredo Petrosino, Alessio Ferone
    Pages 57-73
  4. R. A. Aliev, W. Pedrycz, O. H. Huseynov, L. M. Zeinalova
    Pages 117-153
  5. Alberto Fernández, Victoria López, María José del Jesus, Francisco Herrera
    Pages 155-184
  6. Giovanna Castellano, Anna Maria Fanelli, Corrado Mencar
    Pages 185-202
  7. Junzo Watada, Takayuki Kawaura, Hao Li
    Pages 203-218
  8. Y. T. Hsiao, T. L. Huang, S. Y. Chang
    Pages 219-235
  9. Yungho Leu, Chien-Pang Lee, Chen-Chia Hung
    Pages 237-248
  10. Back Matter

About this book


Information granules are fundamental conceptual entities facilitating perception of complex phenomena and contributing to the enhancement of human centricity in intelligent systems. The formal frameworks of information granules and information granulation comprise fuzzy sets, interval analysis, probability, rough sets, and shadowed sets, to name only a few representatives. Among current developments of Granular Computing, interesting options concern information granules of higher order and of higher type. The higher order information granularity is concerned with an effective formation of information granules over the space being originally constructed by information granules of lower order. This construct is directly associated with the concept of hierarchy of systems composed of successive processing layers characterized by the increasing levels of abstraction. This idea of layered, hierarchical realization of models of complex systems has gained a significant level of visibility in fuzzy modeling with the well-established concept of hierarchical fuzzy models where one strives to achieve a sound tradeoff between accuracy and a level of detail captured by the model and its level of interpretability. Higher type information granules emerge when the information granules themselves cannot be fully characterized in a purely numerical fashion but instead it becomes convenient to exploit their realization in the form of other types of information granules such as type-2 fuzzy sets, interval-valued fuzzy sets, or probabilistic fuzzy sets. Higher order and higher type of information granules constitute the focus of the studies on Granular Computing presented in this study. The book elaborates on sound methodologies of Granular Computing, algorithmic pursuits and an array of diverse applications and case studies in environmental studies, option price forecasting, and power engineering.



Computational intelligence Granular computing Information granules Intelligent systems

Editors and affiliations

  • Witold Pedrycz
    • 1
  • Shyi-Ming Chen
    • 2
  1. 1.Department of Electrical & Computer EngineeringUniversity of AlbertaEdmontonCanada
  2. 2.Department of Computer Science and Information EngineeringNational Taiwan University of Science and Technology, TaipeiTaiwan

Bibliographic information

  • Book Title Granular Computing and Intelligent Systems
  • Book Subtitle Design with Information Granules of Higher Order and Higher Type
  • Editors Witold Pedrycz
    Shyi-Ming Chen
  • Series Title Intelligent Systems Reference Library
  • DOI
  • Copyright Information Springer Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-642-19819-9
  • Softcover ISBN 978-3-642-26800-7
  • eBook ISBN 978-3-642-19820-5
  • Series ISSN 1868-4394
  • Series E-ISSN 1868-4408
  • Edition Number 1
  • Number of Pages VIII, 308
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
  • Buy this book on publisher's site
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