The purpose was that advance railway freight transportation volume anticipation ability, implemented the rationality of railway freight transportation.
目的在于提高铁路货运运量预测能力，实现铁路货运的合理运输。
After analyzing the data on railway freight volume of recent years, the authors establish the railway freight volume forecasting model by use of grey theory.
通过对近年全国铁路货运量的统计数据进行分析，运用灰色理论建立了铁路货运量预测模型。
Meanwhile, the length of time on training sample was determined as the recent complete economic cycle when using artificial neural network for railway freight volume forecasting.
并提出在利用人工神经网络进行铁路货运量预测时，训练样本的时间长度为最近的一个完整经济周期。
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