LincanLi98 / ASTGCN-r-pytorch

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version

ASTGCN

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN)

This is a Pytorch implementation of ASTGCN and MSTCGN. The pytorch version of ASTGCN released here only consists of the recent component, since the other two components have the same network architecture.

Reference

@inproceedings{guo2019attention,
  title={Attention based spatial-temporal graph convolutional networks for traffic flow forecasting},
  author={Guo, Shengnan and Lin, Youfang and Feng, Ning and Song, Chao and Wan, Huaiyu},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={33},
  pages={922--929},
  year={2019}
}

Datasets

Step 1: Download PEMS04 and PEMS08 datasets provided by ASTGCN-gluon version.

Step 2: Process dataset

• on PEMS04 dataset

  python prepareData.py --config configurations/PEMS04_astgcn.conf

• on PEMS08 dataset

  python prepareData.py --config configurations/PEMS08_astgcn.conf

Train and Test

• on PEMS04 dataset

  python train_ASTGCN_r.py --config configurations/PEMS04_astgcn.conf

• on PEMS08 dataset

  python train_ASTGCN_r.py --config configurations/PEMS08_astgcn.conf