基于BP神经网络模型的煤炭物流需求预测研究

Study on Coal Logistics Demand Forecasting Based on BP Neural Network Model

从区域经济与煤炭产业内在关系的视角,对影响煤炭资源富集区物流的各因素进行分析和选择,构建BP神经网络预测模型,并利用Matlab技术对煤炭物流需求进行拟合,随后结合山西省1996-2011年的煤炭物流数据,分别对模型进行预测演练和精度检验,证明该模型应用于煤炭物流需求预测具有可行性和普适性,进一步对2012-2014年的煤炭物流需求进行预测,为现阶段煤炭产业物流的发展提供较为准确的参考。该模型首次采用区域经济指标结合产业发展因素的方法来对煤炭产业物流需求进行预测,在一定程度上反映了煤炭产业发展与煤炭物流需求之间的复杂映射关系,对今后区域内的产业物流需求预测具有重要的指导意义。

In this paper, viewing from the inner relationship between regional economy and the coal industry, we analyzed and selected the various factors influencing the logistics industry of the regions rich in coal resources, built the BP neural network forecasting model and used the Matlab technology in the fitting analysis of the demand for the coal logistics industry. Then in connection with the coal logistics industrial data of Shanxi from 1996 to 2011, we verified the accuracy of the forecasting.