交通运输工程与信息学报2018，Vol.16Issue(2)：50-56,7.DOI:10.3969/j.issn.1672-4747.2018.02.008
铁路旅客购票需求预测模型研究
Forecasting Model for Railway Passenger Ticketing Demand
摘要
Abstract
Railway passenger ticketing demand (RPTD) is the critical basis for a train tickets allocation, RPTD trend in each section performed differently in the pre-sale period. Based on history ticketing data, this paper put forward the concept of average section ticketing intensity (TI) by analyzing the ticketing distribution during the pre-sale period. The TI was applied to describe the dynamic ticket demand of each origin-destination (OD). The critical characteristic variables of passenger ticketing behavior, such as advance ticketing days, purchasing channel, the number of tickets for once purchasing, travel OD and ticket price, were taken as the attribute vectors which affected forecasting date. A prediction model of nonlinear regression support vector machine was proposed for forecasting the daily tickets demand for each OD in the pre-sale period. Finally, the feasibility of the model was verified by an example.关键词
铁路旅客/购票需求/平均购票强度/支持向量机/预测Key words
railway passenger/ticketing demand/average ticketing intensity/support vector machine(SVM)/forecasting分类
交通工程引用本文复制引用
刘帆洨,彭其渊..铁路旅客购票需求预测模型研究[J].交通运输工程与信息学报,2018,16(2):50-56,7.基金项目
中国铁路总公司科技研究开发计划(2016X008-J) （2016X008-J）
中国铁路总公司科技研究开发计划重大课题(Z2017-X002) （Z2017-X002）
