Spatial-Temporal Dynamic Graph Attention Networks for Ride-hailing Demand Prediction

no code implementations • 7 Jun 2020 • Weiguo Pian, Yingbo Wu, Xiangmou Qu, Junpeng Cai, Ziyi Kou

However, existing GCN-based ride-hailing demand prediction methods only assign the same importance to different neighbor regions, and maintain a fixed graph structure with static spatial relationships throughout the timeline when extracting the irregular non-Euclidean spatial correlations.

Graph Attention Traffic Prediction

STDI-Net: Spatial-Temporal Network with Dynamic Interval Mapping for Bike Sharing Demand Prediction

no code implementations • 7 Jun 2020 • Weiguo Pian, Yingbo Wu, Ziyi Kou

As an economical and healthy mode of shared transportation, Bike Sharing System (BSS) develops quickly in many big cities.