SWIFT

SWIFT: State-space Wavelet Integrated Forecasting Technology for Enhanced Time Series Prediction

This is an official implementation of [SWIFT: State-space Wavelet Integrated Forecasting Technology for Enhanced Time Series Prediction].

Author(s)

Wei Li, Shanghai University;

Prerequisites

Ensure you are using Python 3.9 and install the necessary dependencies by running:

pip install -r requirements.txt

Data set preparation

Due to the storage space limitations of GitHub, some data sets may need to be downloaded separately. However, some small data sets have been included in the repository for demonstration purposes. If you encounter any issues with the data sets, please contact us via email.

Citation

If you find this repo useful, please cite it as follows:

@inproceedings{li2025swift,
  title={SWIFT: State-space Wavelet Integrated Forecasting Technology for Enhanced Time Series Prediction},
  author={Li, Wei},
  booktitle={International Conference on Artificial Neural Networks},
  year={2025},
  note={to be published}
}

Contact

If you have any questions, please contact liwei008009@163.com or submit an issue.
Due to time constraints, business agreements and intellectual property protection, the implementation of this model is partial. If you are interested in our model, please contact me by email.
This repo model is a simplified model and is allowed for commercial use, but please cite. If you want to use the complete implementation model, you can further negotiate business cooperation, thank you very much for your attention.

Acknowledgement

We extend our gratitude to the following repositories for their valuable code and datasets:

• https://github.com/thuml/Time-Series-Library
• https://github.com/thuml/Autoformer
• https://github.com/Hank0626/WFTNet
• https://github.com/William-Liwei/EnergyPatchTST

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