Abstract
To improve the performance of Wavelet Neural Network (WNN), a hybrid WNN learning algorithm, which is combination of Genetic Algorithm (GA) and Chaos Optimization Algorithm (COA) in a mutual complementarity manner, is proposed. In the algorithm, GA is first used to roughly search the optimal parameters of WNN as a whole, and then COA is adopted to perform the refined search on the basis of the result obtained by GA, which can make remarkable progress in modeling accuracy, learning speed, and overcoming local convergence or precocity. Simulation show its effectiveness.
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