# Handbook of Granular Computing

- Length: 1148 pages
- Edition: 1
- Language: English
- Publisher: Wiley-Interscience
- Publication Date: 2008-08-25
- ISBN-10: 0470035544
- ISBN-13: 9780470035542
- Sales Rank: #7970738 (See Top 100 Books)

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

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

Chapter 1 Interval Computation as an Important Part of Granular Computing: An Introduction

Chapter 2 Stochastic Arithmetic as a Model of Granular Computing

Chapter 3 Fundamentals of Interval Analysis and Linkages to Fuzzy Set Theory

Chapter 4 Interval Methods for Non-Linear Equation Solving Applications

Chapter 5 Fuzzy Sets as a User-Centric Processing Framework of Granular Computing

Chapter 6 Measurement and Elicitation of Membership Functions

Chapter 7 Fuzzy Clustering as a Data-Driven Development Environment for Information Granules

Chapter 8 Encoding and Decoding of Fuzzy Granules

Chapter 9 Systems of Information Granules

Chapter 10 Logical Connectives for Granular Computing

Chapter 11 Calculi of Information Granules. Fuzzy Relational Equations

Chapter 12 Fuzzy Numbers and Fuzzy Arithmetic

Chapter 13 Rough-Granular Computing

Chapter 14 Wisdom Granular Computing

Chapter 15 Granular Computing for Reasoning about Ordered Data: The Dominance-Based Rough Set Approach

Chapter 16 A Uniﬁed Approach to Granulation of Knowledge and Granular Computing Based on Rough Mereology: A Survey

Chapter 17 A Uniﬁed Framework of Granular Computing

Chapter 18 Quotient Spaces and Granular Computing

Chapter 19 Rough Sets and Granular Computing: Toward Rough-Granular Computing

Chapter 20 Construction of Rough Information Granules

Chapter 21 Spatiotemporal Reasoning in Rough Sets and Granular Computing

Part Two Hybrid Methods and Models of Granular Computing

Chapter 22 A Survey of Interval-Valued Fuzzy Sets

Chapter 23 Measurement Theory and Uncertainty in Measurements: Application of Interval Analysis and Fuzzy Sets Methods

Chapter 24 Fuzzy Rough Sets: From Theory into Practice

Chapter 25 On Type 2 Fuzzy Sets as Granular Models for Words

Chapter 26 Design of Intelligent Systems with Interval Type-2 Fuzzy Logic

Chapter 27 Theoretical Aspects of Shadowed Sets

Chapter 28 Fuzzy Representations of Spatial Relations for Spatial Reasoning

Chapter 29 Rough–Neural Methodologies in Granular Computing

Chapter 30 Approximation and Perception in Ethology-Based Reinforcement Learning

Chapter 31 Fuzzy Linear Programming

Chapter 32 A Fuzzy Regression Approach to Acquisition of Linguistic Rules

Chapter 33 Fuzzy Associative Memories and Their Relationship to Mathematical Morphology

Chapter 34 Fuzzy Cognitive Maps

Part Three Applications and Case Studies

Chapter 35 Rough Sets and Granular Computing in Behavioral Pattern Identiﬁcation and Planning

Chapter 36 Rough Sets and Granular Computing in Hierarchical Learning

Chapter 37 Outlier and Exception Analysis in Rough Sets and Granular Computing

Chapter 38 Information Access and Retrieval

Chapter 39 Granular Computing in Medical Informatics

Chapter 40 Eigen Fuzzy Sets and Image Information Retrieval

Chapter 41 Rough Sets and Granular Computing in Dealing with Missing Attribute Values

Chapter 42 Granular Computing in Machine Learning and Data Mining

Chapter 43 On Group Decision Making, Consensus Reaching, Voting, and Voting Paradoxes under Fuzzy Preferences and a Fuzzy Majority: A Survey and a Granulation Perspective

Chapter 44 FuzzJADE: A Framework for Agent-Based FLCs

Chapter 45 Granular Models for Time-Series Forecasting

Chapter 46 Rough Clustering