The Fuzzy Systems Handbook
Concepts, Designs and Implementation
Academic Press
Published on 1. February 1994
Book
Mixed media product
512 pages
978-0-12-194270-0 (ISBN)
Article exhausted; check for reprint
Description
"The Fuzzy Systems Handbook" provides an introduction to fuzzy logic, the fast-growing alternative to binary logic that has wide applications from computer science to process control. This handbook leads the reader through the complete process of designing, constructing, implementing, verifying and maintaining a platform-independent fuzzy-system model. It is written in a tutorial style that assumes no background in fuzzy logic on the reader's part. This pack: includes an IBM DOS diskette, with all the book's examples implemented in C++ code; provides mathematically straightforward exposition, with emphasis on practical applications; presents case studies on fraud detection, entropy, managed health care and metallurgical analysis. It features a foreword by Lotfi Zadeh, who developed fuzzy logic in the 1960s.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Professional and scholarly
Illustrations
glossary, bibliography, index
Dimensions
Height: 241 mm
Width: 190 mm
Weight
1178 gr
ISBN-13
978-0-12-194270-0 (9780121942700)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Earl Cox | Michael O'Hagan
The Fuzzy Systems Handbook
A Practitioner's Guide to Building, Using, and Maintaining Fuzzy Systems
Book
10/1998
2nd Edition
AP Professional
€55.70
Article is exhausted; no reprint
Content
Fuzzy systems and fuzzy models; the fuzzy world model; fuzzy sets; fuzzy logic; approximate reasoning; constructing a fuzzy system model; case studies and advanced fuzzy system modelling techniques; fuzzy database and objectbase operations; N-dimensional fuzzy models; adaptive fuzzy systems models; fuzzy models with multiple experts; hybrid fuzzy and neural co-operating systems; model stability; validation and performancce metrics; production systems installation and maintenance.