mirror of https://github.com/czzhangheng/STDEN.git
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| configs | ||
| lib | ||
| model | ||
| .gitignore | ||
| LICENSE | ||
| README.md | ||
| requirements.txt | ||
| stden_eval.py | ||
| stden_train.py | ||
README.md
STDEN
This is the implementation of Spatio-temporal Differential Equation Network (STDEN) in the following paper: Jiahao Ji, Jingyuan Wang, Zhe Jiang, Jiawei Jiang, and Hu Zhang, Towards Physics-guided Neural Networks for Traffic Flow Prediction, AAAI 2022.
The training framework of this project comes from chnsh. Thanks a lot :)
Requirement
- scipy>=1.5.2
- numpy>=1.19.1
- pandas>=1.1.5
- pyyaml>=5.3.1
- pytorch>=1.7.1
- future>=0.18.2
- torchdiffeq>=0.2.0
Dependency can be installed using the following command:
pip install -r requirements.txt
Model Traning and Evaluation
One can run the code by
# traning for dataset GT-221
python stden_train.py --config_filename=configs/stden_gt.yaml
# testing for dataset GT-221
python stden_eval.py --config_filename=configs/stden_gt.yaml
The configuration file of all datasets are as follows:
| dataset | config file |
|---|---|
| GT-221 | stden_gt.yaml |
| WRS-393 | stden_wrs.yaml |
| ZGC-564 | stden_zgc.yaml |
Note the data is not public and I am not allowed to distribute it.