Research on sales forecasting based on ARIMA and BP neural network combined model

A single ARIMA model cannot meet higher standards of prediction accuracy. Moreover, it can only deal with small prediction periods in the forecasting work. For the sake of prediction accuracy, we combined an ARIMA model with BP neural network. Firstly, an ARIMA forecasting model is established. Secondly the BP neural network is used to improve the single ARIMA model. The residual of ARIMA model is trained and fitted by BP neural network. Finally, more accurate results are given through combination with the forecast results of ARIMA model. The practice turns out that, compared with single ARIMA model, the prediction accuracy of new ARIMA model improved by BP neural networks is obviously enhanced, with an average error of forecast decreasing 10.4% by a large margin. Thus, the combined model proposed by this paper can be used in future prediction researches and industrial data analysis.