SWMM GNN metamodel – Code for paper: Transferable and Data Efficient Metamodeling of Storm Water System Nodal Depths Using Auto-Regressive Graph Neural Networks

DOI:10.4121/989a0d3d-3b4d-47c7-8677-31c5975f9dec.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/989a0d3d-3b4d-47c7-8677-31c5975f9dec
Datacite citation style:
Garzón, Alexander; Kapelan, Zoran ; Langeveld, Jeroen; Taormina, Riccardo (2024): SWMM GNN metamodel – Code for paper: Transferable and Data Efficient Metamodeling of Storm Water System Nodal Depths Using Auto-Regressive Graph Neural Networks. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/989a0d3d-3b4d-47c7-8677-31c5975f9dec.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

Repository of the code for the GNN based metamodel of SWMM. This code is linked to the paper "Transferable and Data Efficient Metamodeling of Storm Water System Nodal Depths Using Auto-Regressive Graph Neural Networks" by Alexander Garzón, Zoran Kapelan, Jeroen Langeveld, and Riccardo Taormina.

This repository contains the code for developing machine learning metamodels of SWMM.

In brief, this code allows to create a dataset from SWMM simulations, train a machine learning model, and evaluate the model. The code is designed to work with SWMM simulations of storm water systems. The code is based on PyTorch and PyTorch Geometric.

This work is supported by the TU Delft AI Labs programme.

This repository was supported by the Digital Competence Centre, Delft University of Technology.

History

  • 2024-09-12 first online, published, posted

Publisher

4TU.ResearchData

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Water Management

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/3e58770f-ae91-482a-b9c9-b51fa2692bf0.git "SWMM_GNN_Repository_Paper_version"

Or download the latest commit as a ZIP.