The Fuzzy Systems Handbook: A Practitioner's Guide to Building, Using, and Maintaining Fuzzy Systems - Tapa blanda

From reviews of the First Edition: "When it's time to roll up your sleeves and put fuzzy logic to work, Earl Cox can show you how to put theory into practice. His excellent The Fuzzy Systems Handbook presents a complete fuzzy-modeling system (source code included) and explains how to use it." --Byte Magazine "Unlike many textbooks on fuzzy logic, this book by Earl Cox is a very impressive computer-oriented guide to the world of fuzzy sets and their applications in modelling soft and complex systems...Carefully chosen figures give a rapid and deep insight into the very nature of the problems being discussed...In summary, The Fuzzy Systems Handbook is a valuable source volume for system designers and all those interested in the applications of fuzzy systems." --Control Engineering Practice

Featuring a totorial style and requiring no background in fuzzy logic, this is a comprehensive introduction to fuzzy systems. It leads the reader through the process of designing, constructing, implementing, verifying and maintaining a platform-independent fuzzy system model. This edition has been extensively revised to bring the subject up to date, and features two additional chapters, "Building and using Fuzzy Cognitive map Models", and "Building ME-OWA Models". The multiplatform CD-ROM contains all the C++ source code from the book's examples, and a package of fuzzy systems-related tools and utilities, featuring two notable components. The first is Metus Systems' basic fuzzy modelling software, which includes complete C/C++ source code for creating and executing fuzzy models, a Visual Basic shell that can be used to create fuzzy sets and generate the C/C++ include files, and code for models for pricing, project management, risk assessment and more. The second is a CD-ROM providing the ME-OWA (Minimum-Entropy, Ordered Weighted Aggregation) decision modelling software from Fuzzy Logic Inc. This software is used to focus on a single objective function from a set of alternatives given a fuzzy ranking among various alternatives. It is not only an important technique as a stand-alone tool, but is an important methodology in parameter selection (and parameterization ordering) for generic algorithms and various data miming techniques. It is also used to establish rule and policy level peer weights in fuzzy models. The book adopts a straighforward exposition, with emphasis on practical use.