The successful development and deployment of expert system tools spurred the initial momentum in developing and using intelligent techniques in industry. The brittleness of expert systems and the enormous effort involved in the development and maintenance of knowledge bases prompted researchers to seek friendlier approaches. Neural networks, fuzzy logic, and evolutionary computing tools added a new dimension to the quest for more intelligent tools to supplement the capabilities of expert systems. In one volume, Knowledge-Based Intelligent Techniques in Industry comprehensively brings together the more important developments in the use of intelligent techniques in solving industrial problems.
The book's primary readership includes electrical engineers in industry as well as researchers working in computational intelligence research labs - outlining state-of-the-art techniques and cost-effective solutions.
Knowledge-Based Intelligent Techniques in Industry singularly reflects the increasing study of computational intelligence techniques for designing and monitoring complex, less predictable electrical or mechanical systems.
Table of Contents
An Intelligent Driver Warning System, C.J. Harris, J.M. Roberts and P.E.An
Knowledge-Based Scheduling Techniques in Industry, J. Sauer
Fuzzy Image Analysis for Medical Applications, J. Hiltner, M. Jager, M. Moser and C. Tresp
Fuzzy Logic in Communication Networks, H. Hellendoorn and R.Seising
Fuzzy Logic in Power Supply Applications, A. Bellini, R.Rovatti and M. Scheffler
Intelligent Motor Fault Detection, M.Y.Chow, B. Li and G.Goddu
Self-Organising Manufacturing System Using Genetic Algorithms, T.Fukuda and N.Kubota
Intelligent Telecommunication Technologies, G.Weiss, J. Eddy, S.Weiss and R.Dube
Immune Network-Based Distributed Diagnostic System, M.Kayama
Current and Future Applications of Intelligent Techniques in the Electric Power Industry, A.M.Wildberger