Metaheuristic Procedures for Training Neural Networks

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ISBN-13:
9780387334158
Erscheinungsdatum:
01.05.2006
Seiten:
252
Autor:
Enrique Alba
Gewicht:
558 g
Format:
242x163x19 mm
Serie:
36, Operations Research/Computer S
Sprache:
Englisch
Beschreibung:

This book provides successful implementations of metaheuristic methods for neural network training. It is the first book to achieve this objective. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Overall, the book's aim is to provide a broad coverage of the concepts, methods, and tools of the important area of ANNs within the realm of continuous optimization.
Apart from research efforts bringing together metaheuristic techniques to train artificial neural networks, this is the first book to achieve this objective. This book provides a unified approach to training ANNs with modern heuristics; moreover, it provides abundant literature demonstrating how these procedures escape local optima and solve problems in very different mathematical scenarios
Classical Training Methods.- Local Search Based Methods.- Simulated Annealing.- Tabu Search.- Variable Neighbourhood Search.- Population Based Methods.- Estimation of Distribution Algorithms.- Genetic Algorithms.- Scatter Search.- Other Advanced Methods.- Ant Colony Optimization.- Cooperative Coevolutionary Methods.- Greedy Randomized Adaptive Search Procedures.- Memetic Algorithms.

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