Passenger Flow Status Evaluation in Subway Station Based on Probabilistic Neural Network  

作　　者：SUN Jianhui HU Hua LIU Zhigang 

机构地区：College of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201620, China

出　　处：《International English Education Research》2018年第3期34-37,共4页国际英语教育研究（英文版）

摘　　要：This paper select the escalator with large flow in the station as the object, analysing the correlation of the AFC data of the in and out gates and the passenger flow parameters by passenger flow density and the passing time acquired and calculated in the waiting area of the prediction escalator to select the gates related to the predicted the escalator. NARX neural network is used to predict the model of the passenger flow parameters of the escalator waiting area based on the related gates＇ AFC data, then a probabilistic neural network model was established by using the AFC data and predicted passenger flow parameters as input and the passenger flow status in the escalator waiting area of subway station as output.The result shows the predicting model can predict the passenger flow status of the escalator waiting area better by the AFC data in the subway station. Research result can provide decision basis for the operation management of the subway station.

关 键 词：Subway station Escalator waiting area AFC data Probabilistic neural network Passenger flow status 

分 类 号：U231.4[交通运输工程—道路与铁道工程] TP18[自动化与计算机技术—控制理论与控制工程]