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京沪通道铁路快运需求分析及产品设计

Demand Analysis and Product Design of Beijing-Shanghai Railway Expressway
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摘要 为充分发挥铁路运输优势,对京沪间快运市场需求及铁路快运产品展开研究,运用BP神经网络对货源吸引城市的快运需求量和货流OD进行预测,通过Logit分担率模型计算不同距离下铁路运输的分担率,获得未来年京沪通道既有线和高铁所占市场份额,对京沪通道铁路快运产品进行设计。研究结果表明,京沪通道的快运需求量较大,在快运市场中具有很大的竞争优势,可采用多种运力资源实现资源配置。为应对大规模的快运需求,对装卸场地、装卸作业设备等配套设施设备进行设计,此结果可为京沪通道铁路快运发展提供参考。 In order to give full play to the advantages of railway transportation,the study analyzes the market demands and products of express transportation between Beijing and Shanghai.Firstly,the study predicts the demands and OD of freight flow in cities attracted by freight sources with BP neural network,calculates the share rate of railway transport at different distances with Logit share rate model,obtains the market share of existing lines and high-speed railways in the Beijing-Shanghai Channel in the future,and designs railway express products in the Beijing-Shanghai Channel.The results show that the Beijing-Shanghai Channel has a large demand for express transportation and has great competitive advantages in the express market.A variety of capacity resources can be used to achieve resource allocation.In order to cope with large-scale express transportation needs,supporting facilities and equipment,such as the loading and unloading site,loading and unloading operation equipment,etc.,are designed.The results can provide reference for the development of Beijing-Shanghai railway expressway.
作者 叶杉 李威伦 杨黎朝 Ye Shan;Li Weilun;Yang Lichao(School of Traffic and Transportation,Xi’an Jiaotong Engineering University,Xi’an 710300,China;China Railway First Survey and Design Institute Group Co.,LTD,Xi’an 710043,China)
出处 《黑龙江科学》 2024年第12期52-54,58,共4页 Heilongjiang Science
关键词 京沪通道 快运需求量 Logit分担率模型 BP神经网络 Beijing-Shanghai Channel Express demand Logit share ratio model BP neural network
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