基于模糊C均值聚类的城市轨道交通新线站点进出站客流量预测

Prediction Entrance and Exit Passenger Flow for New Line of Urban Rail Transit Based on Fuzzy C-Means Clustering Methods

对城市轨道交通既有车站的进出站客流量历史数据、车站周边的土地利用性质以及土地利用强度指标进行模糊化处理,基于模糊C均值聚类分析模型对既有站点进出站客流量规律相近的车站进行相似聚类,建立站点进出站客流量与周边的土地利用性质和开发强度的关系模型,并利用该模型对新线站点的进出站客流量进行预测。

In this paper,the historical data of passenger flow in and out of existing metro stations,the land use properties around the stations and the land use intensity index are fuzzified.Based on Fuzzy C-means clustering methods,a approach of station’s entrance and exit passenger flow prediction model is proposed,which characterized with land-use indicators and development intensity.This model is used to predict the passenger flow in and out of the new line station.