The Fuzzy Systems Handbook
A Practitioner's Guide to Building, Using, and Maintaining Fuzzy Systems
- 2nd Edition - October 14, 1998
- Latest edition
- Author: Earl Cox
- Language: English
This new edition provides a comprehensive introduction to fuzzy logic, and leads the reader through the complete process of designing, constructing, implementing, verifying and… Read more
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The multiplatform CD-ROM contains all the C++ source code from the book's examples - but its real value is the robust package of fuzzy system related tools and utilities, featuring two notable components. First: Metus Systems' basic fuzzy modeling 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. Second: The ME-OWA (Minimum-Entropy, Ordered Weighted Aggregation) decision modeling 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 genetic algorithms and various data mining techniques. It is also an important technique used to establish rule and policy level peer weights in fuzzy models.
@bul:* Tutorial style, requiring no background in fuzzy logic
* Case studies illustrate real-world fuzzy applications
* Mathematically straightforward exposition, with emphasis on practical use
* CD-ROM features all the C++ source code from the book and a robust package of fuzzy system related tools and utilities
- Edition: 2
- Latest edition
- Published: October 14, 1998
- Language: English
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Earl Cox
Earl has over thirty years experience in managing and participating in the software development process at the system as well as tightly integrated application level. In the area of advanced machine intelligence technologies, Earl is a recognized expert in fuzzy logic, and adaptive fuzzy systems as they are applied to information and decision theory. He has pioneered the integration of fuzzy neural systems with genetic algorithms and case-based reasoning. As an industry observer and futurist, Earl has written and talked extensively on the philosophy of the Response to Change, the nature of Emergent Intelligence, and the Meaning of Information Entropy in Mind and Machine.