基于灰色遗传BP神经网络的铁路货运量预测  

Forecasting of Railway Freight Volume Based on Grey Genetic BP Neural Network

作　　者：李建国 向万里[2] 王久梗[3] LI Jianguo;XIANG Wanli;WANG Jiugeng(Freight Department,China Railway Lanzhou Group Co.,Ltd.,Lanzhou 730000,China;School of Traffic and Transportation,Lanzhou Jiaotong University,Lanzhou 730070,China;Research Institute of Logistics and Information Technology of Gansu Province,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]中国铁路兰州局集团有限公司,兰州730000 [2]兰州交通大学交通运输学院,兰州730070 [3]兰州交通大学甘肃省物流与信息技术研究院,兰州730070

出　　处：《科技和产业》2022年第1期119-124,共6页Science Technology and Industry

基　　金：国家自然科学基金(61563028);中国国家铁路集团有限公司科技研究开发计划(N2020X015);中国铁路兰州局集团有限公司科技项目(2021013-2,2020010-2,2020011-2)。

摘　　要：铁路货运量受限于社会建设、投资和政策调控等多方面的影响。为了给货运系统提供更好的调配支撑,基于铁路货运量影响因素,加强BP预测性能,提出灰色遗传BP神经网络的铁路货运量预测模型(GR_GA_BP),对铁路货运量进行灰色关联分析,找出与铁路货运量关联程度较高的指标作为GR_GA_BP预测模型的输入对货运量进行预测。通过MAPE、RMSE和MAE对比GR_GA_BP模型与其他模型,实验结果表明,GR_GA_BP模型优于其他模型,可以作为新方法预测和研究铁路货运能力。Railway freight volume is limited by the influence of social construction,investment and policy regulation.In order to provide better deployment support for the freight system,based on the influence factors of railway freight volume and strengthening BP prediction performance,the gray genetic BP is proposed Neural network railway freight volume prediction model(GR_GA_BP).The grey correlation analysis of railway freight volume is used to find out the index with higher correlation with railway freight volume,which is used as GR_GA_The input of BP prediction model predicts the freight volume.By comparing the GR_GA_BP model with other models through MAPE,RMSE and MAE,the experimental results show that the GR_GA_BP model is superior to other models and can be used as a new method to predict and study railway freight capacity.

关 键 词：铁路货运量 评价指标 灰色关联分析 遗传算法 BP神经网络 

分 类 号：U294[交通运输工程—交通运输规划与管理]