Genetic Algorithm and Variable Feed-Forward Neural Networks: Theory and application - Softcover

Ling, Steve

 
9783843367295: Genetic Algorithm and Variable Feed-Forward Neural Networks: Theory and application
Softcover
ISBN 10: 3843367299 ISBN 13: 9783843367295
Verlag: LAP LAMBERT Academic Publishing, 2010

Inhaltsangabe

This book focuses on the real-coded genetic algorithm and different topologies of feed-forward neural networks. Results in the following areas will be reported: (1) a real-coded genetic algorithm with new crossover and mutation operations, and its applications; (2) three different topologies of variable feed-forward neural networks, and their applications to short-term electric load forecasting and hand-written graffiti recognition. The real-coded genetic algorithm (RCGA) is one evolutionary computation technique that can tackle complex optimization problems. In this book, RCGA with new genetic operations called the average-bound crossover (ABX) and wavelet mutation (WM) will be presented. The three proposed topologies of variable feed- forward network networks are: (1) the variable- structure neural network (VSNN), (2) the variable- parameter neural network (VPNN), and (3) the variable-node-to-node-link neural network (VN2NN). By taking advantage of these networks' structures, the learning and generalization abilities of the networks can be increased. All the network parameters are tuned by the RCGA with ABX and WM.

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Reseña del editor

This book focuses on the real-coded genetic algorithm and different topologies of feed-forward neural networks. Results in the following areas will be reported: (1) a real-coded genetic algorithm with new crossover and mutation operations, and its applications; (2) three different topologies of variable feed-forward neural networks, and their applications to short-term electric load forecasting and hand-written graffiti recognition. The real-coded genetic algorithm (RCGA) is one evolutionary computation technique that can tackle complex optimization problems. In this book, RCGA with new genetic operations called the average-bound crossover (ABX) and wavelet mutation (WM) will be presented. The three proposed topologies of variable feed- forward network networks are: (1) the variable- structure neural network (VSNN), (2) the variable- parameter neural network (VPNN), and (3) the variable-node-to-node-link neural network (VN2NN). By taking advantage of these networks' structures, the learning and generalization abilities of the networks can be increased. All the network parameters are tuned by the RCGA with ABX and WM.

Biografía del autor

Steve Ling received the Ph.D. degrees in 2006. Currently, he works in University of Technology, Sydney, Australia as Chancellor’s Postdoctoral Research Fellow (Lecturer). He has authored and coauthored over 70 international journal and conference papers on Computational Intelligence and its industrial applications.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2010
Sprache
Englisch
ISBN 10 
3843367299
ISBN 13 
9783843367295
Einband
Tapa blanda
Anzahl der Seiten
252
Kontakt zum Hersteller
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Verantwortliche Person
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