Optimized BP Neural Network Model Based on Niche Genetic Algorithm

Abstract

According to the shortcomings of BP neural network model, such as slower convergence speed, entrapment in local optimum, unstable network structure etc., and an improved BP neural network model based on niche genetic algorithm (NGA-BP) was presented. The proposed model first makes full use of the global searching ability of genetic algorithm and the nonlinear reflection ability and the association learning ability of BP neural network to optimize the initial connection weights and thresholds of the neural network by means of selection operation, crossover operation, mutation operation and niche pass, and then adopts BP algorithm to train network, which can effectively solve the problems of BP network about unreasonable initial value and network nonconvergence, and improve the convergence speed and the stability of network. The experimental results show that the model is more feasible and effective than the traditional methods.