Metaheuristic procedures for training neural networks
Author(s)
Bibliographic Information
Metaheuristic procedures for training neural networks
（Operations research/computer science interface series, 35）
Springer, c2006
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
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.
by "Nielsen BookData"