Space-Time adaptive network for origin-destination passenger demand prediction

Author:

Xu Haoge,Chen Yong,Li Chuanjia,Chen Xiqun (Michael)

Funder

Natural Science Foundation of Zhejiang Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference43 articles.

1. An encoder framework for taxi-demand prediction using spatio-temporal function approximation;Bhanu;Engineering Applications of Artificial Intelligence,2023

2. BERT-based deep spatial-temporal network for taxi demand prediction;Cao;IEEE Transactions on Intelligent Transportation Systems,2022

3. A novel reinforced dynamic graph convolutional network model with data imputation for network-wide traffic flow prediction;Chen;Transportation Research Part c: Emerging Technologies,2022

4. Chen, S.-A., Li, C.-L., Yoder, N., Arik, S. O., and Pfister, T. (2023). TSMixer: An all-MLP architecture for time series forecasting. Doi: 10.48550/arXiv.2303.06053.

5. A multi-scale unified model of human mobility in urban agglomerations;Chen;Patterns,2023

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