详情

原文传递 Using Data From the Web to Predict Public Transport Arrivals Under Special Events Scenarios

题名：	Using Data From the Web to Predict Public Transport Arrivals Under Special Events Scenarios
其他题名：	Ahas,R.,Kuusik,A.,&Tiru,M.(June,2009).Spatial and temporal variability of tourism loyalty in estonia:Mobile positioning perspective.Proceedings of the Nordic Geographers Meeting(NGM09),Department of Geography,University of Turku,Turku,Finland.
正文语种：	英文
作者：	FRANCISCO C. PEREIRA
关键词：	Data mining;Demand Prediction;Public Transport;Smartcard;Urban Computing;Web Mining
摘要：	The Internet has become the preferred resource to announce, search, and comment about social events such as concerts, sports games, parades, demonstrations, sales, or any other public event that potentially gathers a large group of people. These planned special events often carry a potential disruptive impact to the transportation system, because they correspond to nonhabitual behavior patterns that are hard to predict and plan for. Except for very large and mega events (e.g., Olympic games, football world cup), operators seldom apply special planning measures for two major reasons: The task of manually tracking which events are happening in large cities is labor-intensive; and, even with a list of events, their impact is hard to estimate, especially when more than one event happens simultaneously. In this article, we utilize the Internet as a resource for contextual information about special events and develop a model that predicts public transport arrivals in event areas. In order to demonstrate the feasibility of this solution for practitioners, we apply off-the-shelf techniques both for Internet data collection and for the prediction model development. We demonstrate the results with a case study from the city-state of Singapore using public transport tap-in/tap-out data and local event information obtained from the Internet.
出版年：	2015
论文唯一标识：	J-96Y2015V19N03005
doi：	10.1080/15472450.2013.868284
期刊名称：	Journal of Intelligent Transportation Systems Technology Planning and Operations
拼音刊名(出版物代码)：	J-96
卷：	19
期：	03
页码：	273-288