Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms:...

Features

• Cover Type: Hard Cover with 368 pages
• Published by: CRC
• Edition: 1st Edition November 17, 1998
• Written in: English
• ISBN 10 Number: 0849398045
• ISBN 13 Number: 978-0849398049
• Book Dimensions: 9.2 x 6.1 x 1 inches
• Weighs: 1.5 pounds

Product Description
Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: · direct frequency converters · electro-hydraulic systems · motor control · toaster control · speech recognition · vehicle routing · fault diagnosis · Asynchronous Transfer Mode (ATM) communications networks · telephones for hard-of-hearing people · control of gas turbine aero-engines · telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.

Book Info
Integrates neural networks, fuzzy systems, & evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another.

Reader Reviews
Looking at the content of first 14 pages it seems that this book is going to be a very good reference for the researchers as well as beginers of the Evolutionary computing in Control. The conceptual part is also good as it can help beginers to get in to cognitive approach to the problem as tradinational methods are not useful in real time application and can now only used for comparision. Very Good Approach from the Editors.