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Item Details
Title: FUZZY SETS IN APPROXIMATE REASONING AND INFORMATION SYSTEMS
By: James C. Bezdek (Editor), Didier Dubois (Editor), Henri Prade (Editor)
Format: Paperback

List price: £242.00


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 1461373905
ISBN 13: 9781461373902
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 21 November, 2012
Edition: Softcover reprint of the original 1st ed. 1999
Series: The Handbooks of Fuzzy Sets 5
Pages: 514
Description: Approximate reasoning is a key motivation in fuzzy sets and possibility theory. Fuzzy Sets in Approximate Reasoning and Information Systems is a major source of information for research scholars and graduate students in computer science and artificial intelligence, interested in human information processing.
Synopsis: Approximate reasoning is a key motivation in fuzzy sets and possibility theory. This volume provides a coherent view of this field, and its impact on database research and information retrieval. First, the semantic foundations of approximate reasoning are presented. Special emphasis is given to the representation of fuzzy rules and specialized types of approximate reasoning. Then syntactic aspects of approximate reasoning are surveyed and the algebraic underpinnings of fuzzy consequence relations are presented and explained. The second part of the book is devoted to inductive and neuro-fuzzy methods for learning fuzzy rules. It also contains new material on the application of possibility theory to data fusion. The last part of the book surveys the growing literature on fuzzy information systems. Each chapter contains extensive bibliographical material. Fuzzy Sets in Approximate Reasoning and Information Systems is a major source of information for research scholars and graduate students in computer science and artificial intelligence, interested in human information processing.
Illustrations: XV, 514 p.
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
Some other items by this author:
ADVANCES IN ARTIFICIAL INTELLIGENCE: APPLICATIONS AND THEORY (HB)
ANALYSIS OF FUZZY INFORMATION (HB)
APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION (PB)
APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION IV (PB)
APPLICATIONS OF FUZZY LOGIC TECHNOLOGY III (HB)
COMPUTATIONAL APPROACHES TO ANALOGICAL REASONING: CURRENT TRENDS (HB)
COMPUTATIONAL APPROACHES TO ANALOGICAL REASONING: CURRENT TRENDS (PB)
CONCEPTS AND METHODS OF DECISION-MAKING (HB)
DECISION MAKING PROCESS
DECISION MAKING PROCESS
DECISION MAKING PROCESS
DECISION THEORY AND MULTI-AGENT PLANNING (PB)
ELEMENTARY CLUSTER ANALYSIS
ELEMENTARY CLUSTER ANALYSIS: FOUR BASIC METHODS THAT (USUALLY) WORK (HB)
FOUNDATIONS OF INFORMATION AND KNOWLEDGE SYSTEMS (PB)
FUNDAMENTALS OF FUZZY SETS (HB)
FUNDAMENTALS OF FUZZY SETS (PB)
FUZZY MODELS AND ALGORITHMS FOR PATTERN RECOGNITION AND IMAGE PROCESSING (HB)
FUZZY MODELS AND ALGORITHMS FOR PATTERN RECOGNITION AND IMAGE PROCESSING (PB)
FUZZY SETS AND SYSTEMS (HB)
FUZZY SETS IN APPROXIMATE REASONING AND INFORMATION SYSTEMS (HB)
FUZZY SETS, LOGICS AND REASONING ABOUT KNOWLEDGE (HB)
FUZZY SETS, LOGICS AND REASONING ABOUT KNOWLEDGE (PB)
MATHEMATICAL MODELS FOR HANDLING PARTIAL KNOWLEDGE IN ARTIFICIAL INTELLIGENCE (HB)
MATHEMATICAL MODELS FOR HANDLING PARTIAL KNOWLEDGE IN ARTIFICIAL INTELLIGENCE (PB)
METHODS FOR HANDLING IMPERFECT SPATIAL INFORMATION (HB)
METHODS FOR HANDLING IMPERFECT SPATIAL INFORMATION (PB)
PATTERN RECOGNITION WITH FUZZY OBJECTIVE FUNCTION ALGORITHMS (PB)
PLANNING BASED ON DECISION THEORY (PB)
POSSIBILITY THEORY (HB)
POSSIBILITY THEORY (PB)
PREFERENCES AND SIMILARITIES (HB)
PREFERENCES AND SIMILARITIES (PB)
RANDOM SETS AND RANDOM FUZZY SETS AS ILL-PERCEIVED RANDOM VARIABLES (PB)
SCALABLE UNCERTAINTY MANAGEMENT (PB)
SOFT METHODS FOR HANDLING VARIABILITY AND IMPRECISION (PB)
TRANSACTIONS ON ROUGH SETS (PB)

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