Multi-Attribute Spatial-temporal Graph Convolutional Network for Taxi Demand Forecasting

Author:

Xu Lei1ORCID,Xia Leiming1ORCID,Pan Shourun1ORCID

Affiliation:

1. Qingdao University, China

Publisher

ACM

Reference31 articles.

1. Badr-Eddine Soussi Niaimi , Mohammed Bouhorma , and Hassan Zili . 2022. The Evolution of the Traffic Congestion Prediction and AI Application. Networking, Intelligent Systems and Security 237 (October 2021 ), 19-31. https://doi.org/10.1007/978-981-16-3637-0_2 10.1007/978-981-16-3637-0_2 Badr-Eddine Soussi Niaimi, Mohammed Bouhorma, and Hassan Zili. 2022. The Evolution of the Traffic Congestion Prediction and AI Application. Networking, Intelligent Systems and Security 237 (October 2021), 19-31. https://doi.org/10.1007/978-981-16-3637-0_2

2. A taxi dispatch system based on prediction of demand and destination

3. Transferable Self-Supervised Instance Learning for Sleep Recognition;Zhao Aite;IEEE Transactions on Multimedia. https://doi.org/10.1109/TMM.,2022

4. Zhiqiang Lv , Jianbo Li , Chuanhao Dong , and Zhihao Xu. 2021. DeepSTF: A Deep Spatial-Temporal Forecast Model of Taxi Flow. The Computer Journal (November 2021 ), 1-16. https://doi.org/10.1093/comjnl/bxab178 10.1093/comjnl Zhiqiang Lv, Jianbo Li, Chuanhao Dong, and Zhihao Xu. 2021. DeepSTF: A Deep Spatial-Temporal Forecast Model of Taxi Flow. The Computer Journal (November 2021), 1-16. https://doi.org/10.1093/comjnl/bxab178

5. Multi-city traffic flow forecasting via multi-task learning

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