Handbook of Granular Computing

Handbook of Granular Computing

Editor(s): Witold Pedrycz, Andrzej Skowron, Vladik Kreinovich

Published Online: 16 JUL 2008

Print ISBN: 9780470035542

Online ISBN: 9780470724163

DOI: 10.1002/9780470724163

About this Book

Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest in the topic as it begins to play a key role in bioinformatics, e-commerce, machine learning, security, data mining and wireless mobile computing when it comes to the issues of effectiveness, robustness and uncertainty.

The Handbook of Granular Computing offers a comprehensive reference source for the granular computing community, edited by and with contributions from leading experts in the field.  

  • Includes chapters covering the foundations of granular computing, interval analysis and fuzzy set theory; hybrid methods and models of granular computing; and applications and case studies.
  • Divided into 5 sections: Preliminaries, Fundamentals, Methodology and Algorithms, Development of Hybrid Models and Applications and Case Studies.
  • Presents the flow of ideas in a systematic, well-organized manner, starting with the concepts and motivation and proceeding to detailed design that materializes in specific algorithms, applications and case studies.
  • Provides the reader with a self-contained reference that includes all pre-requisite knowledge, augmented with step-by-step explanations of more advanced concepts.

The Handbook of Granular Computing represents a significant and valuable contribution to the literature and will appeal to a broad audience including researchers, students and practitioners in the fields of Computational Intelligence, pattern recognition, fuzzy sets and neural networks, system modelling, operations research and bioinformatics. 

Table of contents

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  1. Part One: Fundamentals and Methodology of Granular Computing Based on Interval Analysis, Fuzzy Sets and Rough Sets

    1. Chapter 4

      Interval Methods for Non-Linear Equation Solving Applications (pages 81–96)

      Courtney Ryan Gwaltney, Youdong Lin, Luke David Simoni and Mark Allen Stadtherr

    2. Chapter 10

      Logical Connectives for Granular Computing (pages 205–224)

      Erich Peter Klement, Dr. Radko Mesiar, Andrea Mesiarová-Zemánková and Susanne Saminger-Platz

    3. Chapter 12

      Fuzzy Numbers and Fuzzy Arithmetic (pages 249–283)

      Luciano Stefanini, Laerte Sorini and Maria Letizia Guerra

  2. Part Two: Hybrid Methods and Models of Granular Computing

    1. Chapter 22

      A Survey of Interval-Valued Fuzzy Sets (pages 489–515)

      Humberto Bustince, Javier Montero, Miguel Pagola, Edurne Barrenechea and Daniel Gomez

    2. Chapter 24

      Fuzzy Rough Sets: From Theory into Practice (pages 533–552)

      Chris Cornelis, Martine De Cock and Anna Maria Radzikowska

    3. Chapter 34

      Fuzzy Cognitive Maps (pages 755–774)

      Dr. E. I. Papageorgiou and C. D. Stylios

  3. Part Three: Applications and Case Studies

    1. Chapter 38

      Information Access and Retrieval (pages 835–846)

      Gloria Bordogna, Donald H. Kraft and Gabriella Pasi

    2. Chapter 40

      Eigen Fuzzy Sets and Image Information Retrieval (pages 863–872)

      Ferdinando Di Martino, Salvatore Sessa and Hajime Nobuhara

    3. Chapter 45

      Granular Models for Time-Series Forecasting (pages 949–967)

      Marina Hirota Magalhães, Rosangela Ballini and Fernando Antonio Campos Gomide

    4. Chapter 46

      Rough Clustering (pages 969–985)

      Pawan Lingras, S. Asharaf and Cory Butz

    5. Chapter 48

      Rough and Granular Case-Based Reasoning (pages 1005–1036)

      Dr. Simon C.K. Shiu, Professor Sankar K. Pal and Yan Li

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