An optimization method based on the combination of wavelet neural networks(WNN)and Pareto genetic algorithm was proposed

and was applied to the numerical optimization in internal flows.WNN is composed of input layer

hidden layer and output layer.It replaces the commonly used Sigmoid activation function in back propagation(BP) neural networks by Morlet wavelet generating functions in hidden layer.Pareto genetic algorithm has great global optimum ability and optimization efficiency.Generally

it can always gain uniformly-distributed Pareto optimal solution set.Typical algorithm examples indicate that this algorithm can complete approaching and mapping of non-linear function quickly

efficiently and accurately

with great generalization ability.