An Integrated Predicting Model of New-built Regional Logistics Center's Demand Based on the Artificial Neural Network

摘要

In order to predict the scale of logistics demand for a new-built regional center, economic indicators and the other related measuring indicator of the scale for logistics demand is studied. The factor analysis and back propagation (BP) artificial neural network theory are applied to set up a model for predicting the scale of the logistics center's demand. The factor analysis is applied to this model to reduce the number of indicators of the input layer in the BP artificial neural network, and to reduce complexity. Then model is introduced to fit historical data of the scale of new -built a regional logistics center's demand. Finally, a third-layer BP artificial neural network is constructed. This model was applied to predict the scale of the logistics demand in an example and the forecasting result shows that forecasting accuracy of the model is good. It also provides a new way of a new-built regional logistics center's demand forecast.