Regional GDP Prediction Based on Improved BP Neural Network Model

In this paper, an improved BP neural network model is proposed. In the model, the momentum factor can improve the training speed and avoid falling into local minimum. Steepness factor and adaptive learning rate can improve the convergence speed. The genetic algorithm is used to solve the problem of low training speed, low accuracy of prediction and easy to fall into local minimum of BP neural network. Then the improved BP neural network model is established to predict GDP of Anhui province. The result shows that it is better than the other models which are presented in this paper on forecasting GDP of Anhui province.