Short-term inbound rail transit passenger flow prediction based on BILSTM model and influence factor analysis

Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems (ITS). According to previous studies, it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and...

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Bibliographic Details

Published in:	Digital Transportation and Safety
Main Authors:	Qianru Qi, Rongjun Cheng, Hongxia Ge
Format:	Article
Language:	English
Published:	Maximum Academic Press 2023-02-01
Subjects:	rail transit passenger flow predict time travel characteristics bilstm influence factor deep learning model
Online Access:	https://www.maxapress.com/article/doi/10.48130/DTS-2023-0002