Code for our IMWUT/UbiComp'20 paper: D3P: Data-driven Demand Prediction for Fast Expanding Electric Vehicle Sharing Systems
Man Luo, Bowen Du, Konstantin Klemmer, Hongming Zhu, Hakan Ferhatosmanoglu and Hongkai Wen
- python=3.6
- numpy
- pandas
- tensorflow-gpu=1.8.0
- scikit-learn
We've provided sample data in ./data, which can be extracted by:
python data_preparing.py
You could also plug in your own data in the d3p framework.
Generate data:
python seq2avg_data_generation.py
Training:
python seq2avg_train.py
Testing:
python seq2avg_predict.py
Generate data:
python seq2seq_data_generation.py
Training
python seq2seq_train.py
Testing
python seq2seq_predict.py
@article{Luo:IMWUT:2020,
author = {Luo, Man and Du, Bowen and Klemmer, Konstantin and Zhu, Hongming and Ferhatosmanoglu, Hakan and Wen, Hongkai},
title = {D3P: Data-Driven Demand Prediction for Fast Expanding Electric Vehicle Sharing Systems},
year = {2020},
issue_date = {March 2020},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {4},
number = {1},
url = {https://doi.org/10.1145/3381005},
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