Prediction of Daily Entrance and Exit Passenger Flow of Rail Transit Stations by Deep Learning Method
Joint Authors
Yang, Xiaoguang
Zhu, Huaizhong
Wang, Yizhe
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The prediction of entrance and exit passenger flow of rail transit stations is one of key research focuses in the area of intelligent transportation.
Based on the big data of rail transit IC card (Public Transportation Card), this paper analyzes the data of major dynamic factors having effect on entrance passenger flow and exit passenger flow of rail transit stations: weather data, atmospheric temperature data, holiday and festival data, ground index data, and elevated road data and calculates the daily entrance passenger flow and daily exit passenger flow of individual rail transit stations with data reduction.
Furthermore, based on the history data of passenger flow of rail transit stations and relevant influence factors, it applies the deep learning method to choose the relatively optimal hidden layer node by means of the cut-and-try method, set up input data and labeled data, select the activation function and loss function, and use the Adam Gradient Descent Optimization Algorithm for iterative global convergence.
The results verify that this method accurately predicts the daily entrance passenger flow and daily exit passenger flow of rail transit stations with the prediction error of less than 4.1%.
Finally, the proposed model is compared with the linear regression model.
American Psychological Association (APA)
Zhu, Huaizhong& Yang, Xiaoguang& Wang, Yizhe. 2018. Prediction of Daily Entrance and Exit Passenger Flow of Rail Transit Stations by Deep Learning Method. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1181497
Modern Language Association (MLA)
Zhu, Huaizhong…[et al.]. Prediction of Daily Entrance and Exit Passenger Flow of Rail Transit Stations by Deep Learning Method. Journal of Advanced Transportation No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1181497
American Medical Association (AMA)
Zhu, Huaizhong& Yang, Xiaoguang& Wang, Yizhe. Prediction of Daily Entrance and Exit Passenger Flow of Rail Transit Stations by Deep Learning Method. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1181497
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181497