ASTGCN-r-pytorch-master-2019.zip

# ASTGCN Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) <img src="fig/ASTGCN architecture.png" alt="image-20200103164326338" style="zoom:50%;" /> 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 ```latex @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](https://github.com/guoshnBJTU/ASTGCN/tree/master/data). Step 2: Process dataset - on PEMS04 dataset ```shell python prepareData.py --config configurations/PEMS04_astgcn.conf ``` - on PEMS08 dataset ```shell python prepareData.py --config configurations/PEMS08_astgcn.conf ``` # Train and Test - on PEMS04 dataset ```shell python train_ASTGCN_r.py --config configurations/PEMS04_astgcn.conf ``` - on PEMS08 dataset ```shell python train_ASTGCN_r.py --config configurations/PEMS08_astgcn.conf ```