Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search. The second part of the book presents population based methods, such as Estimation Distribution algorithms, Scatter Search, and Genetic Algorithms. The third part covers other advanced techniques, such as Ant Colony Optimization, Co-evolutionary methods, GRASP, and Memetic algorithms. Overall, the book’s objective is engineered to provide a broad coverage of the concepts, methods, and tools of this important area of ANNs within the realm of continuous optimization.
Enrique Alba & Rafael Martí
Metaheuristic Procedures for Training Neural Networks [PDF ebook]
Metaheuristic Procedures for Training Neural Networks [PDF ebook]
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Lingua Inglese ● Formato PDF ● Pagine 252 ● ISBN 9780387334165 ● Dimensione 12.4 MB ● Editore Enrique Alba & Rafael Martí ● Casa editrice Springer US ● Città NY ● Paese US ● Pubblicato 2006 ● Scaricabile 24 mesi ● Moneta EUR ● ID 2144801 ● Protezione dalla copia DRM sociale