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铁路车-货实时追踪影响因素研究
引用本文:钱琳,关梦园,王凤琳,黄睿.铁路车-货实时追踪影响因素研究[J].铁路计算机应用,2021,30(3):40-44.
作者姓名:钱琳  关梦园  王凤琳  黄睿
作者单位:中国铁道科学研究院集团有限公司 电子计算技术研究所,北京 100081
基金项目:国家重点研发计划(2018YFB1201403)
摘    要:针对铁路车-货实时追踪及预警系统中车-货全程追踪匹配率不高的问题,对货物运输过程各环节中影响车-货追踪匹配效果的因素进行分析,提出针对性措施;通过整合货运制票信息、货物装卸信息及集装箱装载清单信息,改进车-货匹配算法,建立整车的车-货、集装箱的车-货-箱的匹配关系,将车-货全程追踪匹配率提升至95%以上。系统充分利用既有货物运输数据,通过信息整合和集成运用,为货物运输的调度指挥、分析决策提供更为完整的数据,有助于提升铁路货运服务质量。

关 键 词:货车追踪  货物追踪  车-货匹配  匹配率  影响因素分析
收稿时间:2020-08-04

Research on influence factors of real-time tracking of railway freights loaded on wagons
Affiliation:Institute of Computing Technologies, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China
Abstract:To tackle the problem of low ratio of freight-wagon matching in the real-time tracking and early-warn system of railway freights loaded on wagons, the factors that affect the effect of real-time tracking of freights loaded on wagons in the process of railway freight transpot are analyzed respectively. Through integrating freight bill data, freight handling data and container loading list data and improving the algorithm of freight-wagon matching, the matching relationships of wagon-freight and wagon-container-freight are established, thus enhancing the freight-wagon matching ratio to over 95%. The system is improved by utilizing available freight transport data and can provide more integral data for dispatching and command, analysis and decision-making of freight transport, helping further improve the service quality of railway freight transport.
Keywords:
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