%0 Journal Article
%T 土地利用混合度对轨道交通车站客流的影响
%A 李俊芳
%A 姚敏峰
%A 季峰
%A 向蕾
%J 同济大学学报(自然科学版)
%D 2016
%R 10.11908/j.issn.0253-374x.2016.09.016
%X 针对土地利用混合程度如何影响轨道交通车站客流的问题，建立非线性回归方法对其进行量化研究.采用递远递减权重和相邻车站重叠区域人口分配权重来计算加权人口，并以车站客流/加权人口作为因变量，从而分析由土地利用混合程度引起的车站客流变化.构建最小二乘支持向量机模型来分析土地利用混合程度、岗位居住人口比以及车站客流间相互关系.最后，以日本东京都109个车站的实际数据进行案例分析，案例结果表明土地利用混合程度对车站客流影响较弱，而岗位居住人口比与车站出站客流呈现显著正相关.因此，客流预测过程中应以岗位居住人口比代替土地利用混合程度作为关键因素.</br>This essay focuses on how land use mix quantitatively impacts urban rail transit ridership at station level by nonlinear regression model. Distance decay weight and weight of population in mutual service area assigned to each station are used to weigh population within service area of station. Then ridership divided by weighted population is taken as dependent variable to analyze what is the relationship between land use mix and ridership at station level. Least square support vector machine is the ideal model to do the above thing. Finally, data of 109 stations in Tokyo, Japan are taken as case study, result of which shows land use mix has a little influence on ridership at station level and meanwhile, employment/inhabitants within service area of station has a significant influence on ridership at station level. So, employment/inhabitants should substitute land use mix and be taken as key predictor for ridership at station level
%K 交通工程 车站客流预测 最小二乘支持向量机 土地利用混合程度 岗位居住人口比&lt
%K /br&gt
%K traffic engineering ridership forecasting at station level least squares support vector machine (LS SVM) land use mix ratio of employment to inhabitant
%U http://tjxb.cnjournals.cn/ch/reader/view_abstract.aspx?file_no=15526&flag=1