Titlebook: Metaheuristic Procedures for Training Neural Networks; Enrique Alba,Rafael Martí Book 2006 Springer-Verlag US 2006 Approximation.algorithm

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Simulated Annealing optimization problems. In this chapter we show how it can be used to train artificial neural networks by examples. Experimental results indicate that good results can be obtained with little or no tuning.

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Tabu Searchomponents of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore the hallmark of tabu search approaches, founded on a quest for “integrating principles,” by which alternative forms of memory are appropriately combined with e

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Ant Colony Optimizationesent the general description of ACO, as well as its adaptation for the application to continuous optimization problems. We apply this adaptation of ACO to optimize the weights of feed-forward neural networks for the purpose of pattern classification. As test problems we choose three data sets from

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Cooperative Coevolutionary Methodsorks that must cooperate to form a solution for a specific problem, instead of evolving complete networks. The combination of these subnetworks is part of a coevolutionary process. The best combinations of subnetworks must be evolved together with the coevolution of the subnetworks. Several subpopul

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