In traditional BP or GA to identify the application of fuzzy neural network in convergence of easily falling into local minimum problem of low recognition rate is proposed A hybrid genetic algorithm based on BFGS and its basic idea is first to construct a feedforward fuzzy and genetic algorithm is used to evolve neural network structure for several generations When the gradient of the objective function or norm less than the preset value is used to optimize BFGS algorithm recognition experiment compared the algorithm GA The recognition accuracy of fast convergence speed is improved about 7 recognition can be applied to a class of fuzzy neural networks

A hybrid.pdf

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