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E-raamat: Handbook of Granular Computing

Edited by Andrzej Skowron (Warsaw University), Edited by Vladik Kreinovich (University of Texas), Edited by Witold Pedrycz (University of Alberta)

Formaat: PDF+DRM
Ilmumisaeg: 31-Jul-2008
Kirjastus: Wiley-Interscience
Keel: eng
ISBN-13: 9780470724156

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Artificial intelligence

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Formaat: PDF+DRM
Ilmumisaeg: 31-Jul-2008
Kirjastus: Wiley-Interscience
Keel: eng
ISBN-13: 9780470724156

Teised raamatud teemal:

Artificial intelligence

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This extremely large and comprehensive handbook on granular computing traces this relatively new discipline's roots in artificial intelligence, interval computing and quotient space theory and explores the growing interest in this subject due to advances in bioinformatics, data mining, wireless technologies and e-commerce. Pedrycz (computational intelligence, U. of Alberta, Canada), Skowron (mathematics and computer science, Warsaw U., Poland) and Kreinovich (mathematics and computer science, U. of Texas) have edited information from leading computing experts on the basics of fuzzy set theory, interval analysis and hybrid methodologies. Students and practitioners of system modeling, operations research and bioinfomatics should gain a more robust understanding of cutting-edge research in the field, especially in terms computational intelligence and neural networks. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)

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.

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

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

Vladik Kreinovich

2 Stochastic Arithmetic as a Model of Granular Computing

R. Alt and J. Vignes

3 Fundamentals of Interval Analysis and Linkages to Fuzzy Set Theory

Weldon A. Lodwick

4 Interval Methods for Non-Linear Equation Solving Applications

C. Ryan Gwaltney, Youdong Lin, Luke D. Simoni, and Mark A. Stadtherr

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

Witold Pedrycz

6 Measurement and Elicitation of Membership Functions

Taner Bilgiç and İ. Burhan Türkşen

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

Paulo Fazendeiro and José Valente de Oliveira

8 Encoding and Decoding of Fuzzy Granules

Shounak Roychowdhury

9 Systems of Information Granules

F. Hoeppner

10 Logical Connectives for Granular Computing

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

11 Calculi of Information Granules. Fuzzy Relational Equations

Siegfried Gottwald

12 Fuzzy Numbers and Fuzzy Arithmetic

Luciano Stefanini, Laerte Sorini, and Maria Letizia Guerra

13 Rough-Granular Computing

Andrzej Skowron and James F. Peters

14 Wisdom Granular Computing

Andrzej Jankowski and Andrzej Skowron

15 Granular Computing for Reasoning about Ordered Data: The Dominance-Based

Rough Set Approach

Salvatore Greco, Benedetto Matarazzo, and Roman Slowiński

16 A Unified Approach to Granulation of Knowledge and Granular Computing

Based on Rough Mereology: A Survey

Lech Polkowski

17 A Unified Framework of Granular Computing

Y. Yao

18 Quotient Spaces and Granular Computing

Ling Zhang and Bo Zhang

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

Andrzej Skowron and Jaroslaw Stepaniuk

20 Construction of Rough Information Granules

Anna Gomolińska

21 Spatiotemporal Reasoning in Rough Sets and Granular Computing

Piotr Synak

Part Two Hybrid Methods and Models of Granular Computing

22 A Survey of Interval-Valued Fuzzy Sets

H. Bustince, J. Montero, M. Pagola, E. Barrenechea, and D. Gomez

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

Leon Reznik

24 Fuzzy Rough Sets: From Theory into Practice

Chris Cornelis, Martine De Cock, and Anna Maria Radzikowska

25 On Type 2 Fuzzy Sets as Granular Models for Words

Jerry M. Mendel

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

Oscar Castillo and Patricia Melin

27 Theoretical Aspects of Shadowed Sets

G. Cattaneo and D. Ciucci

28 Fuzzy Representations of Spatial Relations for Spatial Reasoning

Isabelle Bloch

29 Rough–Neural Methodologies in Granular Computing

Sushmita Mitra and Mohua Banerjee

30 Approximation and Perception in Ethology-Based Reinforcement Learning

James F. Peters

31 Fuzzy Linear Programming

J. Ramík

32 A Fuzzy Regression Approach to Acquisition of Linguistic Rules

Junzo Watada and Witold Pedrycz

33 Fuzzy Associative Memories and Their Relationship to Mathematical Morphology

Peter Sussner and Marcos Eduardo Valle

34 Fuzzy Cognitive Maps

E.I. Papageorgiou and C.D. Stylios

Part Three Applications and Case Studies

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

J.G. Bazan

36 Rough Sets and Granular Computing in Hierarchical Learning

Sinh Hoa Nguyen and Hung Son Nguyen

37 Outlier and Exception Analysis in Rough Sets and Granular Computing

Tuan Trung Nyuyen

38 Information Access and Retrieval

Gloria Bordogna, Donald H. Kraft, and Gabriella Pasi

39 Granular Computing in Medical Informatics

G. Bortolan

40 Eigen Fuzzy Sets and Image Information Retrieval

Ferdinando Di Martino, Salvatore Sessa, and Hajime Nobuhara

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

Jerzy W. Grzymala-Busse

42 Granular Computing in Machine Learning and Data Mining

E. Huellermeier

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

J. Kacprzyk, S. Zadrożny, M. Fedrizzi and H. Nurmi

44 FuzzJADE: A Framework for Agent-Based FLCs

Vincenzo Loia and Mario Veniero

45 Granular Models for Time-Series Forecasting

M. Magalhaes, R. Ballini, and F. Gomide

46 Rough Clustering

Pawan Lingras, S. Asharaf, and Cory Butz

47 Rough Document Clustering and The Internet

Hung Son Nguyen and Tu Bao Ho

48 Rough and Granular Case-Based Reasoning

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

49 Granulation in Analogy-Based Classification

Arkadiusz Wojna

50 Approximation Spaces in Conflict Analysis: A Rough Set Framework

Sheela Ramanna

51 Intervals in Finance and Economics: Bridge between Words and Numbers, Language of Strategy

M. Tarrazo

52 Granular Computing Methods in Bioinformatics

J.J. Valdés

Index

Witold Pedrycz is a Professor and Canada Research Chair (CRC) in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences. He is actively pursuing research in Computational Intelligence, fuzzy modeling, knowledge discovery and data mining, fuzzy control including fuzzy controllers, pattern recognition, knowledge-based neural networks, relational computation, bioinformatics, and Software Engineering. He has published numerous papers in this area. He is also an author of 9 research monographs covering various aspects of Computational Intelligence and Software Engineering.

Andrzej Skowron holds a Ph.D. degree in Mathematical Foundations of Computer Science from the University of Warsaw in Poland, Doctor of Science (Habilitation) degree in Mathematical Foundations of Computer Science from the University of Warsaw in Poland. In 1991 he received the Scientific Title of Professor. Andrzej Skowron is the author and co-author of more than 280 scientific publications, 15 edited books and several special issues of international journals.

Vladik Kreinovich Department of Computer Science University of Texas. He received his M.S. in Mathematics and Computer Science from St. Petersburg University, Russia, in 1974, and Ph.D. from the Institute of Mathematics, Soviet Academy of Sciences, Published 6 books and more than 600 papers. Member of the editorial board of the international journal "Reliable Computing" (formerly, "Interval Computations"), and several other journals. Co-maintainer of the international website on interval computations.

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