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Fuzzy Sets, Rough Sets, Multisets and Clustering

  • Book
  • © 2017

Overview

Editors:
  1. Vicenç Torra

    1. University of Skövde, School of Informatics University of Skövde, Skövde, Sweden

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  2. Anders Dahlbom

    1. University of Skövde, School of Informatics University of Skövde, Skövde, Sweden

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  3. Yasuo Narukawa

    1. Toho Gakuen , Tokyo, Japan

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  • Dedicated to Prof. Sadaaki Miyamoto
  • Presents state-of-the-art papers on clustering, multisets, rough sets and fuzzy sets
  • All contributions were written by respected experts in the field
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 671)

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Table of contents (20 chapters)

  1. Front Matter

    Pages i-x
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  2. On This Book: Clustering, Multisets, Rough Sets and Fuzzy Sets

    • Vicenç Torra, Yasuo Narukawa, Anders Dahlbom
    Pages 1-5

  3. Clustering and Classification

    1. Front Matter

      Pages 7-7
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    2. Contributions of Fuzzy Concepts to Data Clustering

      • Sadaaki Miyamoto
      Pages 9-28

    3. Fuzzy Clustering/Co-clustering and Probabilistic Mixture Models-Induced Algorithms

      • Katsuhiro Honda
      Pages 29-43

    4. Semi-supervised Fuzzy c-Means Algorithms by Revising Dissimilarity/Kernel Matrices

      • Yuchi Kanzawa
      Pages 45-61

    5. Various Types of Objective-Based Rough Clustering

      • Yasunori Endo, Naohiko Kinoshita
      Pages 63-85

    6. On Some Clustering Algorithms Based on Tolerance

      • Yukihiro Hamasuna, Yasunori Endo
      Pages 87-99

    7. Robust Clustering Algorithms Employing Fuzzy-Possibilistic Product Partition

      • László Szilágyi
      Pages 101-121

    8. Consensus-Based Agglomerative Hierarchical Clustering

      • José Luis García-Lapresta, David Pérez-Román
      Pages 123-135

    9. Using a Reverse Engineering Type Paradigm in Clustering. An Evolutionary Programming Based Approach

      • Jan W. Owsiński, Janusz Kacprzyk, Karol Opara, Jarosław Stańczak, Sławomir Zadrożny
      Pages 137-155

    10. On Hesitant Fuzzy Clustering and Clustering of Hesitant Fuzzy Data

      • Laya Aliahmadipour, Vicenç Torra, Esfandiar Eslami
      Pages 157-168

    11. Experiences Using Decision Trees for Knowledge Discovery

      • Eva Armengol, Àngel García-Cerdaña, Pilar Dellunde
      Pages 169-191

  4. Bags, Fuzzy Bags, and Some Other Fuzzy Extensions

    1. Front Matter

      Pages 193-193
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    2. L-Fuzzy Bags

      • Fateme Kouchakinejad, Mashaallah Mashinchi, Radko Mesiar
      Pages 195-219

    3. A Perspective on Differences Between Atanassov’s Intuitionistic Fuzzy Sets and Interval-Valued Fuzzy Sets

      • Eulalia Szmidt, Janusz Kacprzyk
      Pages 221-237

  6. Fuzzy Sets and Decision Making

    1. Front Matter

      Pages 275-275
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Keywords

About this book

This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making.

The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.

Editors and Affiliations

  • University of Skövde, School of Informatics University of Skövde, Skövde, Sweden

    Vicenç Torra, Anders Dahlbom

  • Toho Gakuen , Tokyo, Japan

    Yasuo Narukawa

Bibliographic Information

  • Book Title: Fuzzy Sets, Rough Sets, Multisets and Clustering

  • Editors: Vicenç Torra, Anders Dahlbom, Yasuo Narukawa

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-47557-8

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2017

  • Hardcover ISBN: 978-3-319-47556-1Published: 19 January 2017

  • Softcover ISBN: 978-3-319-83767-3Published: 29 April 2018

  • eBook ISBN: 978-3-319-47557-8Published: 13 January 2017

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: X, 347

  • Number of Illustrations: 25 b/w illustrations, 15 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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