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Metaheuristic Procedures for Training Neural Networks, Vol. 36 Book

Metaheuristic Procedures for Training Neural Networks, Vol. 36
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  • Metaheuristic Procedures for Training Neural Networks, Vol. 36
  • Written by author Enrique Alba
  • Published by Springer-Verlag New York, LLC, May 2006
  • Artificial neural networks (ANNs) offer a general framework for representing non-linear mappings from several input variables to several output variables, and they can be considered as an extension of the many conventional mapping techniques. In addition
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Authors

Contributing Authors     ix
Preface     1
Introduction
Classical Training Methods   E. Soria   J.D. Martin   P. Lisboa     7
Local Search Based Methods
Simulated Annealing   E. Aarts   P. v.der Horn   J. Korst   W. Michiels   H. Sontrop     37
Tabu Search   F. Glover   R. Marti     53
Variable Neighbourhood Search   J.A. Moreno Perez   N. Mladenovic   B. Melian Batista   I. G. del Amo     71
Population Based Methods
Estimation of Distribution Algorithms   J. Madera   B. Dorronsoro     87
Genetic Algorithms   E. Alba   F. Chicano     109
Scatter Search   M. Laguna   R. Marti     139
Other Advanced Methods
Ant Colony Optimization   K. Socha   C. Blum     153
Cooperative Coevolutionary Methods   N. Garcia-Pedrajas   C. Hervas-Martinez   D. Ortiz-Boyer     181
Greedy Randomized Adaptive Search Procedures   F.R. Angel-Bello   J. Luis Gonzalez-Velarde   A.M. Alvarez     207
Memetic Algorithms   N. Krasnogor   A. Aragon   J. Pacheco     225
Index     249


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