基于大数据的城际客流实时监控

Zheng Li, Yan Wang, Qinghai Chen
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引用次数: 0

摘要

管理人口流动是城市增长和可持续发展的关键。本研究使用了来自多个可信赖和公开的公共交通网站的行政和商业数据,以实时方式获取客流。用一个案例研究来说明应用程序,按公共交通方式(铁路或航空),按铁路服务类型和时间划分城际客流。此外,还开发了一个监测人口流动影响的模型,可作为政府和决策者管理人口流动的决策支持工具。公共交通乘客运动的大数据方法具有以下特点:(1)成本低;(2)人口规模大;(3)数据采集/更新即时;(4)质量高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Monitoring of Intercity Passenger Flows Based on Big Data
Managing population mobility is a key to urban growth and sustainable development. This study uses administrative and business data from a number of trustworthy and publicly-available websites for public transport to access passenger flows in a real-time manner. A case study is used to illustrate the application, with intercity passenger flows by public transport mode (rail or air), by rail service type and by time. Moreover, a model is developed for monitoring the implications of population movements, which can be a decision support tool for governments and policy makers to manage population mobility. The big-data approach to accessing public transport passenger movement has the following characteristics: (1) low cost, (2) a population scale, (3) instantaneous data collection/update, and (4) high quality.
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