Granular, Fuzzy, and Soft Computing / edited by Tsau-Young Lin, Churn-Jung Liau, Janusz Kacprzyk.

Format:

Book

Contributor:

Lin, Tsau Y., 1937- editor.

Liau, Churn-Jung, editor.

Kacprzyk, Janusz, editor.

Series:

Encyclopedia of Complexity and Systems Science Series, 2629-2343

Language:

English

Subjects (All):

Mathematics.

Coding theory.

Information theory.

Computational intelligence.

Data mining.

Artificial intelligence.

Big data.

Applications of Mathematics.

Coding and Information Theory.

Computational Intelligence.

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Big Data.

Local Subjects:

Applications of Mathematics.

Coding and Information Theory.

Computational Intelligence.

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Big Data.

Physical Description:

1 online resource (936 pages)

Edition:

1st ed. 2023.

Place of Publication:

New York, NY : Springer US : Imprint: Springer, 2023.

Summary:

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. .

Contents:

Cooperative Multi-hierarchical Query Answering Systems

Dependency and Granularity in Data -Mining

Fuzzy Logic

Fuzzy Probability Theory

Fuzzy System Models Evolution from Fuzzy Rulebases to Fuzzy Functions

On Genetic-Fuzzy Data Mining Techniques

Granular Computing and Data Mining for Ordered Data: The Dominance-Based Rough Set Approach

Granular Computing, Information Models for

Granular Computing, Introduction to

Granular Computing and Modeling of the Uncertainty in Quantum Mechanics

Philosophical Foundation for Granular Computing

Granular Computing: Practices, Theories, and Future Directions

Granular Computing, Principles and Perspectives of

Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities

Granular Model for Data Mining

Granular Neural Networks

Granulation of Knowledge: Similarity Based Approach in Information and Decision Systems

Multi-Granular Computing and Quotient Structure

Non-standard Analysis, An Invitation to

Information System Design Using Fuzzy and Rough Set Theory

Rough Set Data Analysis.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Lin, Tsau Young Granular, Fuzzy, and Soft Computing

ISBN:

1-0716-2628-0

OCLC:

1374427506