The Prediction of Stock Index Based on Genetic Algorithm Optimized Chaotic Neural Network

In order to improve forecasting model accuracy of BP neural network for chaotic time series,an improved prediction method for chaotic time series of optimized BP neural network based on genetic algorithm ( GA) was presented. In this method,the BP neural network topology was constructed by the number of input and output of time series. The GA was used to optimize the weights and thresholds of BP neural network,and then BP neural network was trained to search for the optimal solution. The availability of the proposed prediction method was proved by predicting the time series of Shanghai stock index. The computer simulations have shown that the nonlinear fitting and accuracy of the modified prediction methods were better than BP prediction methods.