/GSNet

AAAI 2021. GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting

Primary LanguagePython

GSNet

AAAI 2021. GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting

Usage

train model on NYC:

python train.py --config config/nyc/GSNet_NYC_Config.json --gpus 0

train model on Chicago:

python train.py --config config/chicago/GSNet_Chicago_Config.json --gpus 0

Configuration

The configuration file config.json contains three parts: Data, Training and Predict:

About

If you find this repository useful in your research, please cite the following paper:

@inproceedings{Wang2021gsnet,
  title={GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting},
  author={Beibei Wang, Youfang Lin,Shengnan Guo, Huaiyu Wan},
  booktitle={2021 AAAI Conference on Artificial Intelligence (AAAI'21)},
  year={2021} 
}