Spatiotemporal multi-graph convolutional networks with synthetic data for traffic volume forecasting

Author:

Zhu Kun,Zhang Shuai,Li Jiusheng,Zhou Di,Dai Hua,Hu Zeqian

Funder

National Natural Science Foundation of China

Zhejiang Province Natural Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference57 articles.

1. Bai, S. J., Kolter, J. Z., & Koltun, V. (2018). An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271.

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3. Geometric deep learning: Going beyond Euclidean data;Bronstein;IEEE Signal Processing Magazine,2017

4. Bruna, J., Zaremba, W., Szlam, A., & LeCun, Y. (2013). Spectral networks and locally connected networks on graphs. arXiv preprint arXiv:1312.6203.

5. Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions;Castro-Neto;Expert Systems with Applications,2009

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