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大秦铁路煤炭运输需求分析与预测
引用本文:倪继娜,张巍,张栋.大秦铁路煤炭运输需求分析与预测[J].铁道货运,2020(1):49-54.
作者姓名:倪继娜  张巍  张栋
作者单位:中国铁道科学研究院研究生部;中国铁道科学研究院集团有限公司运输及经济研究所;中国铁道科学研究院集团有限公司铁道建筑研究所
基金项目:中国铁路总公司科技研究开发计划课题(P2018X011);中国铁道科学研究院集团有限公司科研项目(2018YJ103)
摘    要:随着国家优化存量资源配置、能源结构调整、“公转铁”等政策的相继出台,以及浩吉铁路开通、唐呼铁路能力逐步释放,重载铁路运输需求分布发生变化,大秦铁路作为“西煤东运”的主要重载铁路运输通道,其需求情况也随之发生变化。在阐述大秦铁路上、下游行业发展和运输需求现状的基础上,从宏观经济、市场供需、竞争环境及铁路内部等方面分析影响大秦铁路煤炭运输需求的关键因素,结合大秦铁路煤炭运输需求关键影响因素,构建人工神经网络模型,预测大秦铁路煤炭运输需求。研究大秦铁路煤炭运输需求变化,对决策项目投入、保障货运增量具有重要意义。

关 键 词:大秦铁路  重载运输  运输需求  预测  人工神经网络模型

A Study on the Analysis and Forecast of Coal Transportation Demand on Datong-Qinhuangdao Railway
NI Ji’na,ZHANG Wei,ZHANG Dong.A Study on the Analysis and Forecast of Coal Transportation Demand on Datong-Qinhuangdao Railway[J].Railway Freight Transport,2020(1):49-54.
Authors:NI Ji’na  ZHANG Wei  ZHANG Dong
Institution:(Postgraduate Department,China Academy of Railway Sciences,Beijing 100081,China;Transportation&Economics Research Institute,China Academy of Railway Sciences Co.,Ltd.,Beijing 100081,China;Railway Engineering Research Institute,China Academy of Railway Sciences Co.,Ltd.,Beijing 100081,China)
Abstract:Against the backdrop of the successive introduction of the national policies of“Improving Existence Resource Allocation”,“Energy Restructuring”and“Shifting Transport from Road to Rail”,the opening of Haolebaoji-Ji’an Railway,the gradual capacity release of Tangshan-Hohhot Railway and the changes of demand distribution for heavy-haul railway transportation,the demand for Datong-Qinhuangdao Railway,a major heavy-haul railway transportation channel on the“Coal Transportation from West to East China”network,is changing.Based on an overview of the status quo of the upstream and downstream industry development and transportation demand for Datong-Qinhuangdao Railway,this paper analyzes the key factors affecting the transportation demand from the perspectives of macroeconomics,market supply and demand,external and internal environment.According to the influencing factors,this paper establishes an artificial neural network model to predict the demand,which is of significance to decide project investment and increase volume.
Keywords:Datong-Qinhuangdao Railway  Heavy-Haul Transportation  Transportation Demand  Forecast  Artificial Neural Network Model
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