An in-depth exploration of fuzzy logic methods and practice in information engineering Fuzzy Information Engineering is the first book devoted exclusively to applications of fuzzy logic in information sciences at large. Written by an international team of experts, it takes you on a guided tour through the most important fuzzy set theory applications of the past several years. Each chapter covers a different application of fuzzy logic, and addresses set theory, methodology, and implementation. Here is your opportunity to explore and learn from cutting-edge applications in: * Fault diagnosis * Medical image processing * Internet information retrieval * Chemical process engineering * Data fusion * Learning from data * Freehand drawing * Decision support in investment problems * Music analysis * Scheduling in production management * Satellite image classification * Query processing in databases * Virtual reality * And more The first, in-depth introduction to one of the most important new applications of fuzzy logic, Fuzzy Information Engineering is an indispensable resource for intelligent systems researchers and developers.
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Höhe: 160 mm
Breite: 240 mm
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978-0-471-14766-4 (9780471147664)
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DIDIER DUBOIS and HENRI PRADE are CNRS research scientists at IRIT Institute of Paul Sabatier University, in Toulouse, France. RONALD R. YAGER is Director of the Machine Intelligence Institute at Iona College, in New Rochelle, New York.
Partial table of contents: CLARIFYING INFORMATION: SENSING AND ENHANCING. Elicitation, Pooling, and Assessment of Expert Opinion in the Possibilistic Framework (S. Sandri). CLARIFYING INFORMATION: ABSTRACTING AND MODELING. Learning from Imperfect Data (B. Bouchon-Meunier, et al.). RETRIEVING INFORMATION: QUERYING. Extending SQL Retrieval Features for the Handling of Flexible Queries (P. Bosc & O. Pivert). A Fuzzy SQL Summary Language for Data Discovery (D. Rasmussen & R. Yager). RETRIEVING INFORMATION: REASONING. Fuzzy Set Methods in Inheritance Networks (R. Yager). EXPLOITING INFORMATION: DECISION-MAKING. Operators in Models of Decision Making (H. Zimmermann). Risk Management with Imprecise Information (K. Engermann, et al.). EXPLOITING INFORMATION: DESIGNING AND OPTIMIZING. Fuzzy Scheduling: Principles and Experiments (H. Fargier). Index.
