摘要
以中国进出口商品交易会(广交会)为研究对象,对大型活动期间地铁车站客流组成及其分布特征进行了分析,并基于历史客流数据提出广交会期间车站客流量的提取方法。基于灰色预测理论构建了广交会期间地铁车站客流量预测模型,依托2018年秋季广交会期间地铁车站客流数据对该模型进行了验证。结果表明,所提方法可高精度预测广交会期间的地铁车站客流量。
Taking China Import and Export Fair(CICF)as the study object,the event-related passenger flow composition and distribution characteristics are analyzed.Then,based on historical passenger flow data,the extraction method of station passenger flow during CICF is proposed.On this basis,a metro station passenger flow forecast model during CICF is estimated by using the grey prediction theory,and the model is verified according the metro station passenger flow data of the autumn CICF in 2018.The results show that the proposed method can effectively predict the metro station passenger flow during CICF.
作者
梁强升
LIANG Qiangsheng(Guangzhou Metro Group Co.,Ltd.,510330,Guangzhou,China)
出处
《城市轨道交通研究》
北大核心
2021年第10期196-199,共4页
Urban Mass Transit
