Source codes for Activity-aware human mobility prediction with hierarchical graph attention recurrent network., published in IEEE Transactions on Intelligent Transportation Systems (TITS) in 2024.
- python == 3.6
- torch == 1.7.0+cu110
- mpu == 0.23.1
See requirements.txt for more details.
NYC and Tokyo Check-in Dataset.
Please refer to this repo.
python train.py
Please cite our paper if you use the model in your own work:
@article{tang2022hgarn,
title={HGARN: Hierarchical Graph Attention Recurrent Network for Human Mobility Prediction},
author={Tang, Yihong and He, Junlin and Zhao, Zhan},
journal={arXiv preprint arXiv:2210.07765},
year={2022}
}
We refer to some of the data processing codes in this repo.