Synopses & Reviews
This new edition provides a comprehensive introduction to fuzzy logic, and leads the reader through the complete process of designing, constructing, implementing, verifying and maintaining a platform-independent fuzzy system model. The book has been extensively revised to bring the subject up-to-date, and features two new 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 - 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.
Key Features
* 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
Review
e 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
Synopsis
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."
"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 modeling 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
This new edition provides a comprehensive introduction to fuzzy logic, and leads the reader through the complete process of designing, constructing, implementing, verifying and maintaining a platform-independent fuzzy system model. The book has been extensively revised to bring the subject up-to-date, and features two new 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 - 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 inparameter 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.
Features:
- 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
Synopsis
technique as a stand-alone tool, but is an important methodology inparameter 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.
Features:
- 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
Synopsis
opy, 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 inparameter 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.
Features:
- 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
Table of Contents
Introduction. Fuzziness and Certainty. Fuzzy Sets. Fuzzy Set Operators. Fuzzy Set Hedges. Fuzzy Reasoning. Fuzzy Models. Fuzzy Systems: Case Studies. Building Fuzzy Systems. Using the Fuzzy Code Libraries. Building and Using Fuzzy Cognitive Map Models. Building ME-OWA Models. Glossary. Bibliography. Index.