GCN-Transformer for short-term passenger flow prediction on holidays in urban rail transit systems. (arXiv:2203.00007v2 [cs.LG] UPDATED)

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 prediction rail systems transformer transit