基于大数据平台的线网中心运营指挥系统的运营指标分析技术  

Operation Index Analytic Technology of Train Control Center System Based on Big Data Platform

作　　者：胡波 李冰[1,2] 陈莉莉 周映江[3] HU Bo;LI Bing;CHEN Lili;ZHOU Yingjiang(NARI Group Corporation(State Grid Electric Power Research Institute),210003,Nanjing,China)

机构地区：[1]南瑞集团(国网电力科学研究院)有限公司,南京210003 [2]国电南瑞科技股份有限公司,南京210061 [3]南京邮电大学自动化学院,南京210023

出　　处：《城市轨道交通研究》2018年第11期16-20,共5页Urban Mass Transit

基　　金：国家自然科学基金青年项目(61603196);中国博士后科学基金资助项目(2015M581842);江苏省自然科学基金青年项目(BK20150851)

摘　　要：在城市轨道交通运营管理中,如何通过线网中心运营指挥系统提升运营指标综合分析及辅助决策得到越来越多的关注。对基于大数据平台的地铁线网中心运营指挥系统的运营指标分析技术进行了研究。通过与传统的数据仓库进行对比,得出通过大数据平台的数据统计及数据挖掘可以更深程度地揭示数据之间的关联,为后续运营指标分析提供基础。以车站进站量及车站内温度这一对运营指标为例,通过确定数据分析的一些规则及使用数据挖掘算法——Apriori算法,得出进站量与站内温度之间相互变化的关系,并通过关联对温度变化趋势进行预测,从而为后期预调温度进行能效管理提供有力的理论支撑。In the management of urban rail transit,more and more attentions are paid on how to improve the comprehensive analysis and auxiliary decision-making for the operation index through the network TCC system.In this paper,the key analytic technology of metro network TCC based on big data platform is studied.Compared with the traditional data warehouse,it is concluded that the data statistics and data mining through the big data platform can reveal the correlation between data and provide a basis for the subsequent operation index analysis.Taking the station incoming volume and station temperature as a set of operation index,their relationship is obtained by determining some data analysis rules and using the data mining Apriori algorithm.This method can predict the temperature changing trend through the correlation analysis,and provide a strong theoretical support for the energy efficiency management of preconditioning temperature on later stage.

关 键 词：城市轨道交通 线网中心运营指挥系统 大数据平台 运营指标分析 

分 类 号：F530.7[经济管理—产业经济]