Web: http://arxiv.org/abs/2203.00007

May 6, 2022, 1:12 a.m. | Shuxin Zhang, Jinlei Zhang, Lixing Yang, Jiateng Yin, Ziyou Gao

cs.LG updates on arXiv.org arxiv.org

The short-term passenger flow prediction of the urban rail transit system is
of great significance for traffic operation and management. The emerging deep
learning-based models provide effective methods to improve prediction accuracy.
However, most of the existing models mainly predict the passenger flow on
general weekdays, while few studies focus on predicting the holiday passenger
flow, which can provide more significant information for operators because
congestions or accidents generally occur on holidays. To this end, we propose a
deep learning-based …

arxiv flow on prediction rail systems transformer

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