HSN-LSTM
This code is the implementation of our paper (A Hybrid Spiking Neurons Embedded LSTM Network for Multivariate Time Series Learning under Concept-drift Environment).
Environment version
PyTorch = 1.6
Usage
Example:
You can run the pm25_HSN_LSTM.py file directly to implement the PM2.5 Air Quality forecasting task.
Then, you can execute the following command:
python pm25_HSN_LSTM.py
Note that since this is experimental code, you will need to manually set some parameters in the code, such as the time window and the size of the forecast horizons.
References
If you are interested, please cite this paper.
@ARTICLE{HSN_LSTM, author={Zheng, Wendong and Zhao, Putian and Chen, Gang and Zhou, Huihui and Tian, Yonghong}, journal={IEEE Transactions on Knowledge and Data Engineering}, title={A Hybrid Spiking Neurons Embedded LSTM Network for Multivariate Time Series Learning under Concept-drift Environment}, year={2022}, pages={1-14}, doi={10.1109/TKDE.2022.3178176}}