Passenger Flow Prediction Model of the Newly Constructed Urban Rail Transit Line

ICLEM 2014 ◽  
2014 ◽  
Author(s):  
Zhipeng Wang
Keyword(s):  
Prediction Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Passenger Flow ◽  
Flow Prediction ◽  
Urban Rail

scholarly journals Short-term passenger flow forecast for urban rail transit based on multi-source data

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wei Li ◽  
Liying Sui ◽  
Min Zhou ◽  
Hairong Dong
Keyword(s):  
Traffic Flow ◽  
Urban Traffic ◽  
Urban Rail Transit ◽  
Support Vector ◽  
Rail Transit ◽  
Short Term ◽  
Passenger Flow ◽  
Flow Prediction ◽  
Urban Rail ◽  
Svm Model

AbstractShort-term passenger flow prediction in urban rail transit plays an important role because it in-forms decision-making on operation scheduling. However, passenger flow prediction is affected by many factors. This study uses the seasonal autoregressive integrated moving average model (SARIMA) and support vector machines (SVM) to establish a traffic flow prediction model. The model is built using intelligent data provided by a large-scale urban traffic flow warning system, such as accurate passenger flow data, collected using the Internet of things and sensor networks. The model proposed in this paper can adapt to the complexity, nonlinearity, and periodicity of passenger flow in urban rail transit. Test results on a Beijing traffic dataset show that the SARI-MA–SVM model can improve accuracy and reduce errors in traffic prediction. The obtained pre-diction fits well with the measured data. Therefore, the SARIMA–SVM model can fully charac-terize traffic variations and is suitable for passenger flow prediction.

A Novel Prediction Model for the Inbound Passenger Flow of Urban Rail Transit

2021 ◽  
Author(s):  
Xin Yang ◽  
Qiuchi Xue ◽  
Xingxing Yang ◽  
Haodong Yin ◽  
Yunchao Qu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Passenger Flow ◽  
Urban Rail

scholarly journals The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method

2013 ◽  
Vol 05 (04) ◽  
pp. 227-231 ◽  
Author(s):  
Qian Li ◽  
Yong Qin ◽  
Ziyang Wang ◽  
Zhongxin Zhao ◽  
Minghui Zhan ◽  
...  
Keyword(s):  
Prediction Method ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Passenger Flow ◽  
Flow Prediction ◽  
Urban Rail

Passenger Flow Forecast of Urban Rail Transit Based on Support Vector Regression

2013 ◽  
Vol 433-435 ◽  
pp. 612-616 ◽  
Author(s):  
Bin Xia ◽  
Fan Yu Kong ◽  
Song Yuan Xie
Keyword(s):  
Support Vector Regression ◽  
Risk Function ◽  
Urban Rail Transit ◽  
Support Vector ◽  
Rail Transit ◽  
Risk Minimization ◽  
Promising Alternative ◽  
Minimization Principle ◽  
Passenger Flow ◽  
Urban Rail

This study analyses and compares several forecast methods of urban rail transit passenger flow, and indicates the necessity of forecasting short-term passenger flow. Support vector regression is a promising method for the forecast of passenger flow because it uses a risk function consisting of the empirical error and a regularized term which is based on the structural risk minimization principle. In this paper, the prediction model of urban rail transit passenger flow is constructed. Through the comparison with BP neural networks forecast methods, the experimental results show that applying this method in URT passenger flow forecasting is feasible and it provides a promising alternative to passenger flow prediction.

Operation Organization at Urban Rail Transit Station under Large Passenger Flow

2012 ◽  
Vol 253-255 ◽  
pp. 1995-2000
Author(s):  
Qiao Mei Tang ◽  
Li Ping Shen ◽  
Xian Yong Tang
Keyword(s):  
Transport Process ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Common Condition ◽  
Urban Transit ◽  
Passenger Flow ◽  
Operation Process ◽  
Urban Rail ◽  
Transit Station ◽  
Transit Operation

large passenger flow is a common condition of urban transit operation, and the station bears the pressure of large passenger flow directly. This paper analyzes the reason for the appearance of large passenger flow and the characteristics of it, discusses the principles and methods that the station can apply under large passenger flow combined with the passenger’s transport process and the operation process.

Sign in / Sign up

Export Citation Format

Share Document