Mass Rapid Transit System Passenger Traffic Forecast Using a Re-Sample Recurrent Neural Network
Joint Authors
Xue, Xingsi
Hu, Rong
Chiu, Yi-Chang
Hsieh, Chih-Wei
Zou, Fumin
Liao, Lyuchao
Chang, Tang-Hsien
Source
Journal of Advanced Transportation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-05-12
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
In this study, we developed a model re-sample Recurrent Neural Network (RRNN) to forecast passenger traffic on Mass Rapid Transit Systems (MRT).
The Recurrent Neural Network was applied to build a model to perform passenger traffic prediction, where the forecast task was transformed into a classification task.
However, in this process, the training dataset usually ended up being imbalanced.
To address this dataset imbalance, our research proposes re-sample Recurrent Neural Network.
A case study of the California Mass Rapid Transit System revealed that the model introduced in this work could timely and effectively predict passenger traffic of MRT.
The measurements of passenger traffic themselves were also studied and showed that the new method provided a good understanding of the level of passenger traffic and was able to achieve prediction accuracy upwards of 90% higher than standard tests.
The development of this model adds value to the methodology of traffic applications by employing these Recurrent Neural Networks.
American Psychological Association (APA)
Hu, Rong& Chiu, Yi-Chang& Hsieh, Chih-Wei& Chang, Tang-Hsien& Xue, Xingsi& Zou, Fumin…[et al.]. 2019. Mass Rapid Transit System Passenger Traffic Forecast Using a Re-Sample Recurrent Neural Network. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1170253
Modern Language Association (MLA)
Hu, Rong…[et al.]. Mass Rapid Transit System Passenger Traffic Forecast Using a Re-Sample Recurrent Neural Network. Journal of Advanced Transportation No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1170253
American Medical Association (AMA)
Hu, Rong& Chiu, Yi-Chang& Hsieh, Chih-Wei& Chang, Tang-Hsien& Xue, Xingsi& Zou, Fumin…[et al.]. Mass Rapid Transit System Passenger Traffic Forecast Using a Re-Sample Recurrent Neural Network. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1170253
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170253