摘要
文中利用BP神经网络构建货运量需求预测模型,依据历史货运量数据建立BP神经网络,对其进行训练和学习形成预测模型。该模型能够揭示与货运量相关变量之间的非线性映射关系,通过对相关变量的训练预测出未来的货运量,经过实例分析证明基于神经网络的货运量预测模型是行之有效的。
The main intension of this paper is to structure the quantity of shipments forecast model which used by the BP neural networks. Judging by the history data of quantity of shipments that builds BP neural networks, and builds model by training and studying. The model turn to reveal the nonlinearity mapping relation between the variable being related to quantity of shipments. Through correlated variable＇s training can forecast future quantity of shipments. The example analysis proof that the quantity of shipments forecast model which structured by BP neural network is effective.
出处
《物流工程与管理》
2009年第3期28-29,31,共3页
Logistics Engineering and Management
关键词
货运量
BP神经网络
网络模型
quantity of shipments
BP neural networks
net model
