Published March 29, 2024
| Version v1.0.0
Software
Open
FloodSformer: python code
Authors/Creators
- 1. University of Parma
-
2.
Nvidia (United States)
Description
This is the official implementation of our paper: Pianforini et al. (2024). Real-Time Flood Maps Forecasting for Dam-Break Scenarios with a Transformer-Based Deep Learning Model. Journal of Hydrology, 635, 131169. https://doi.org/10.1016/j.jhydrol.2024.131169
In this repository, we provide the PyTorch code for training and testing out proposed FloodSformer (FS) model.
Detailed information on the repository content are provided in the README.md file.
Acknowledgements
This research was granted by University of Parma through the action “Bando di Ateneo 2022 per la ricerca” co-funded by MUR-Italian Ministry of Universities and Research - D.M. 737/2021 - PNR - PNRR – NextGenerationEU.
Renato Vacondio and Susanna Dazzi acknowledge financial support from the PNRR MUR project ECS_00000033_ECOSISTER.
Files
mpianforini/FloodSformer-v1.0.0.zip
Additional details
Related works
- Is supplement to
- Software: https://github.com/mpianforini/FloodSformer/tree/v1.0.0 (URL)
- Dataset: 10.5281/zenodo.10878384 (DOI)
Software
- Programming language
- Python
References
- Pianforini, M., Dazzi, S., Pilzer, A., & Vacondio, R. (2024). Real-time flood maps forecasting for dam-break scenarios with a transformer-based deep learning model. Journal of Hydrology, 635, 131169. https://doi.org/10.1016/J.JHYDROL.2024.131169