基于灰色-马尔科夫预测模型的售票窗口客流量预测研究

A Study on Passenger Volume Forecast at the Ticketing Counter based on Gray-Markov Forecast Mode

由于每天购票客流量不同,导致铁路售票窗口开放数也不同,提前预测每天的购票客流量成为研究的关键。为系统全面地对售票窗口优化问题进行研究,采用灰色-马尔科夫预测模型对兰州站非高峰期的客流量进行预测,确定将来某一天的客流量,并对比分析灰色-马尔科夫预测模型的预测结果与灰色预测模型的结果,发现基于灰色-马尔科夫预测模型得到的客流量比较接近实际值,表明在求解售票窗口客流量预测问题上,灰色-马尔科夫预测模型具有一定的可行性与有效性,可以提高铁路客运站整体工作效率,促使铁路客运服务质量得到大幅度提升。

Due to the different daily ticket purchasing flow,the number of ticket counters opening is also different,so predicting the daily passenger flow is the key point of this research.To study the optimization of ticket window systematically and comprehensively,this paper uses the gray-Markov forecast model to predict the off-peak traffic at Lanzhou station to determine the passenger flow on a certain day in the future.Comparing the results of gray-Markov forecast model with those of the gray forecast model,it is found that the passenger flow is closer to the actual value based on grey-Markov forecast model,which indicates that the grey-Markov forecast model is feasible and effective in solving the problem of passenger flow prediction in ticket counter.It can improve the overall working efficiency of railway passenger stations and greatly improve the quality of railway passenger service.