Design of Order Demand Forecasting System Based on Neural Network

Abstract

As the market demand is seasonal and random, the traditional data model can not describe the order change rules accurately. In order to improve the prediction accuracy, neural network and gray theory are combined to construct a gray neural network order forecasting method. Gray system theory can capture the regularity of data sequence effectively. The optimal neural network parameters are obtained by training the data set. In the neural network model, enter a small amount of data to achieve accurate prediction of the order. The simulation results show that the improved gray neural network improves the prediction accuracy of the order requirement and provides the basis for the forecast of the market demand compared with the traditional forecasting method.