1 code implementation • 22 Mar 2023 • Siyuan Feng, Taijie Chen, Yuhao Zhang, Jintao Ke, Zhengfei Zheng, Hai Yang
In addition, the existing simulators still face many challenges, ranging from their closeness to real environments of ride-sourcing systems, to the completeness of different tasks they can implement.
no code implementations • 30 Jun 2021 • Zhengfei Zheng, Xu Geng, Hai Yang
Therefore, a comprehensive and multifaceted dataset is required to enable more extensive studies in urban computing.
1 code implementation • 17 Oct 2019 • Jintao Ke, Xiaoran Qin, Hai Yang, Zhengfei Zheng, Zheng Zhu, Jieping Ye
To overcome this challenge, we propose the Spatio-Temporal Encoder-Decoder Residual Multi-Graph Convolutional network (ST-ED-RMGC), a novel deep learning model for predicting ride-sourcing demand of various OD pairs.