Multi-Graph Convolutional-Recurrent Neural Network (MGC-RNN) for Short-Term Forecasting of Transit Passenger Flow. (arXiv:2107.13226v2 [cs.LG] UPDATED)

Short-term forecasting of passenger flow is critical for transit management
and crowd regulation. Spatial dependencies, temporal dependencies,
inter-station correlations driven by other latent factors, and exogenous
factors bring challenges to the short-term forecasts of passenger flow of urban
rail transit networks. An innovative deep learning approach, Multi-Graph
Convolutional-Recurrent Neural Network (MGC-RNN) is proposed to forecast
passenger flow in urban rail transit systems to incorporate these complex
factors. We propose to use multiple graphs to encode the spatial and other
heterogenous …

arxiv flow forecasting graph network neural network recurrent neural network rnn transit