Minimizing Combined Sewer Overflows with Online Model-Predictive Reinforcement Learning: A Case Study of the Stormwater Tunnel in Denmark
- Esther Hahyeon Kim(Creator),
- Thomas Dyhre Nielsen(Creator),
- Mohsen Ghaffari(Creator),
- Martijn Goorden(Creator),
- Andreas Holck Høeg-Petersen(Creator),
- Kim Guldstrand Larsen(Creator)
- Aalborg Portland,
- Aalborg University,
- ,
- ,
Dataset:
Dataset Types
Software
Dataset Information
Date made available
2025-06-01Publisher
ZENODODescription
This is an artifact that can help reproduce the experimental results represented in the paper "Minimizing Combined Sewer Overflows with Online Model-Predictive Reinforcement Learning". The package contains models such as SWMM model, UPPAAL STRATEGO model, Historical weather data, and python code to run the experiment.
Cite this dataset
Brief description
Esther Hahyeon Kim, Thomas Dyhre Nielsen, Mohsen Ghaffari, Martijn Goorden, Andreas Holck Høeg-Petersen, Kim Guldstrand Larsen, Andrzej Wasowski. (2025). Minimizing Combined Sewer Overflows with Online Model-Predictive Reinforcement Learning: A Case Study of the Stormwater Tunnel in Denmark. 10.5281/zenodo.14288652