The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social N
Granular, Fuzzy, and Soft Computing
β Scribed by Tsau-Young Lin, Churn-Jung Liau, Janusz Kacprzyk
- Publisher
- Springer
- Year
- 2023
- Tongue
- English
- Leaves
- 936
- Category
- Library
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β¦ Synopsis
The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data.
For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science.
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Table of contents (51 entries)
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Front Matter
Pages i-xxxi
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Cooperative Multi-hierarchical Query Answering Systems
Zbigniew W. Ras, Agnieszka Dardzinska
Pages 1-6
Dependency and Granularity in Data-Mining
Shusaku Tsumoto, Shoji Hirano
Pages 7-17
Fuzzy Logic
Lotfi A. Zadeh
Pages 19-49
Fuzzy Probability Theory
Michael Beer
Pages 51-75
Fuzzy System Models Evolution from Fuzzy Rulebases to Fuzzy Functions
I. Burhan TΓΌrkΕen
Pages 77-95
On Genetic-Fuzzy Data-Mining Techniques
Tzung-Pei Hong, Chun-Hao Chen, Vincent S. Tseng
Pages 97-116
Granular Computing and Data Mining for Ordered Data: The Dominance-Based Rough Set Approach
Salvatore Greco, Benedetto Matarazzo, Roman SΕowiΕski
Pages 117-145
Granular Computing, Information Models for
Steven A. Demurjian, Alberto De la Rosa Algarin, Rishi Knath Saripalle
Pages 147-160
Introduction to Granular Computing
Tsau-Young Lin
Pages 161-166
Granular Computing and Modeling of the Uncertainty in Quantum Mechanics
Kow-Lung Chang
Pages 167-175
Philosophical Foundation for Granular Computing
Zhengxin Chen
Pages 177-197
Granular Computing: Practices, Theories, and Future Directions
Tsau-Young Lin
Pages 199-219
Principles and Perspectives of Granular Computing
Jianchao Han, Nick Cercone
Pages 221-237
Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities
De Wang, Steve Webb, Kyumin Lee, James Caverlee, Calton Pu
Pages 239-250
Granular Model for Data Mining
Anita Wasilewska, Ernestina Menasalvas
Pages 251-264
Granular Neural Networks
Yan-Qing Zhang
Pages 265-277
Granulation of Knowledge: Similarity Based Approach in Information and Decision Systems
Lech Polkowski
Pages 279-310
Multi-Granular Computing and Quotient Structure
Ling Zhang, Bo Zhang
Pages 311-322
Non-standard Analysis, an Invitation to
Wei-Zhe Yang
Pages 323-354
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