摘要
大货主生命周期价值预测是铁路货运营销工作的一个重要环节,利用变量的敏感度分析方法确定影响铁路大货主价值计算的关键变量,并利用这些关键变量构建BP人工神经网络,通过对铁路货运营销的历史样本数据进行学习,可以预测大货主在未来时域的价值。最后用实际数据验证了该BP神经网络的有效性。
Forecasting the lifetime value (LTV) of major goods owners is an essential link in railway freight traffic marketing. Key variables affecting the LTV of major goods owners are determined by the sensitivity analysis method. The BP artificial neural network is constructed on the basis of these key variables to forecast the LTV of major goods owners in the future. Actual data are given to verify the effectiveness of the BP neural network.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2005年第4期20-24,共5页
Journal of the China Railway Society
关键词
铁路运输
BP神经网络
货运营销
生命周期价值
railway transport
BP neural network
freight traffic marketing
lifetime value