Economic forecasting model based on neural network ensemble

In view of the weaknesses of simplex BP neural network for economic forecasting,a new and more effective economic forecasting model called neural network ensemble(NNE) is developed in this paper.NNE can improve the generalization ability through training multiple neural networks and combining their results.According to the economic data of Jiangmen,Guangdong,five neural networks have been trained by adopting Bagging to build a NNE,which is realized by MATLAB 7.0 and employed to forecast GDP.The forecasting results are satisfactory,proving that NNE is superior to simplex neural network.Meanwhile,NNE turns out to be valid and feasible for economic forecasting and can overcome the shortcomings of simplex BP neural network to some degree.