9 citations · 16 across the 3 of their papers we have counts for
4 papers · 1 filter
Towards Effective Fusion and Forecasting of Multimodal Spatio-temporal Data for Smart Mobility
Chenxing Wang
With the rapid development of location based services, multimodal spatio-temporal (ST) data including trajectories, transportation modes, traffic flow and social check-ins are bein…
CDGNet: A Cross-Time Dynamic Graph-based Deep Learning Model for Traffic Forecasting
Yuchen Fang, Yanjun Qin, Haiyong Luo +4
Traffic forecasting is important in intelligent transportation systems of webs and beneficial to traffic safety, yet is very challenging because of the complex and dynamic spatio-t…
DMGCRN: Dynamic Multi-Graph Convolution Recurrent Network for Traffic Forecasting
Yanjun Qin, Yuchen Fang, Haiyong Luo +2
Traffic forecasting is a problem of intelligent transportation systems (ITS) and crucial for individuals and public agencies. Therefore, researches pay great attention to deal with…
STJLA: A Multi-Context Aware Spatio-Temporal Joint Linear Attention Network for Traffic Forecasting
Yuchen Fang, Yanjun Qin, Haiyong Luo +2
Traffic prediction has gradually attracted the attention of researchers because of the increase in traffic big data. Therefore, how to mine the complex spatio-temporal correlations…