Neural Network optimization with a hybrid evolutionary method that combines Particle Swarm and Genetic Algorithms with fuzzy rules

We describe in this paper a new hybrid evolutionary method that combines PSO and GA with fuzzy rules for the optimization of the topology of a Neural Network (NN) for the problem of face recognition. In this case, we used the Yale face database for training the Neural Network. The new evolutionary method combines the advantages of PSO and GA to give us an improved PSO+GA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible.