基于BP神经网络的全社会集装化货物运量预测

BP neural network based volume forecast of wholly social containerized freight

对1995—2012年全社会集装化货物运量进行了统计归纳,利用灰度关联分析法筛选指标,建立了BP神经网络预测模型,并对我国2013—2020年全社会集装化货运需求行了预测。预测结果显示,BP网络模型对历史实际值拟合效果较好,误差较小,表明其具有较高的可靠性和实用性。

We generalize wholly social containerized freight volume from 1995 to 2012. We also screen out indexes with gray correlation analysis method. We further construct BP neural network prediction model, based on which we predict wholly social containerized freight domestic demand,from 2013 to 2020. Prediction results show that BP neural network model has better fitting effect for the actual past value and little error. It demonstrates that the model has higher reliability and practicability.