基于铁路货运大数据的运输效率分析研究
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摘要
根据铁路局现有运输信息系统,提出基于货运大数据的运输效率分析方法,解决线路区间通过能力下降、车站作业效率降低、车辆周转率低等问题。通过搭建Hadoop大数据平台和GIS平台,利用Spark框架、Java编程语言和Sqoop数据传输工具,实现货运大数据的分析和存储、线路通过能力实时分析、车站作业效率实时提示、货车车辆状态全流程分析等功能,实现大数据分析结果与铁路线路图紧密结合和直观展示。
According to the existing railway transportation information system, this paper proposed a method of transportation efficiency analysis based on large data of freight transport to solve the problems such as the decrease of the capacity of line section, the decrease of the efficiency of station operation and the low turnover rate of vehicles. By building Hadoop big data platform and GIS platform, using Spark framework, Java programming language and Sqoop data transmission tools, it was implemented the functions of the analysis and storage of freight transportation big data, real-time analysis of line passing capacity, real-time prompting of station operation efficiency, and full process analysis of freight vehicle status. The close combination and intuitive display of large data analysis results with railway route map were also realized.
According to the existing railway transportation information system, this paper proposed a method of transportation efficiency analysis based on large data of freight transport to solve the problems such as the decrease of the capacity of line section, the decrease of the efficiency of station operation and the low turnover rate of vehicles. By building Hadoop big data platform and GIS platform, using Spark framework, Java programming language and Sqoop data transmission tools, it was implemented the functions of the analysis and storage of freight transportation big data, real-time analysis of line passing capacity, real-time prompting of station operation efficiency, and full process analysis of freight vehicle status. The close combination and intuitive display of large data analysis results with railway route map were also realized.
引文
[1]钟朝文.新形势下提高路局运输效率的研究与对策[D].北京:中国铁道科学研究院,2015,5:4-20.
[2]丁小军.铁路运输效率和运输能力的提升[J].科技创新与应用,2017(35):123-124.
[3]刘兰芬,杨信丰.铁路运输网络通过能力优化利用模型及算法[J].计算机工程与应用,2017,53(22):264-270.
[4]武威.基于Hadoop平台的铁路车流运行径路获取与预测模型及算法研究[D].北京:北京交通大学,2017,3:17-24.
[5]张晓栋.基于铁路货运大数据的重车车流推算关键技术研究[D].北京:北京交通大学,2018,6:25-30.
[6]王同军.中国铁路大数据应用顶层设计研究与实践[J].中国铁路,2017(1):8-16.
[7]马小宁,李平.铁路大数据应用体系架构研究[J].铁路计算机应用,2016,25(9):7-13.
[8]Chen J,Chen D,Huang B.Research on big data information retrieval base on hadoop architecture[C]//IEEE Workshop on Electronics,Computer and Applications.IEEE,2014:492-495.
[9]史天运,刘军,李平,等.铁路大数据平台总体方案及关键技术研究[J].铁路计算机应用,2016,25(9):1-6.
[10]Duan C M.Design of Big Data Processing System Architecture Base on Hadoop under the Cloud Computing[J].Applied Mechanics&Materials,2014(556-562):6302-6306.
[2]丁小军.铁路运输效率和运输能力的提升[J].科技创新与应用,2017(35):123-124.
[3]刘兰芬,杨信丰.铁路运输网络通过能力优化利用模型及算法[J].计算机工程与应用,2017,53(22):264-270.
[4]武威.基于Hadoop平台的铁路车流运行径路获取与预测模型及算法研究[D].北京:北京交通大学,2017,3:17-24.
[5]张晓栋.基于铁路货运大数据的重车车流推算关键技术研究[D].北京:北京交通大学,2018,6:25-30.
[6]王同军.中国铁路大数据应用顶层设计研究与实践[J].中国铁路,2017(1):8-16.
[7]马小宁,李平.铁路大数据应用体系架构研究[J].铁路计算机应用,2016,25(9):7-13.
[8]Chen J,Chen D,Huang B.Research on big data information retrieval base on hadoop architecture[C]//IEEE Workshop on Electronics,Computer and Applications.IEEE,2014:492-495.
[9]史天运,刘军,李平,等.铁路大数据平台总体方案及关键技术研究[J].铁路计算机应用,2016,25(9):1-6.
[10]Duan C M.Design of Big Data Processing System Architecture Base on Hadoop under the Cloud Computing[J].Applied Mechanics&Materials,2014(556-562):6302-6306.