SoftwareApplication
name: SWMM_GNN_Repository_Paper_version
description: SWMM GNN metamodel – Code for paper: Transferable and Data Efficient Metamodeling of Storm Water System Nodal Depths Using Auto-Regressive Graph Neural Networks
description: 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.
code repository: https://data.4tu.nl/v3/datasets/3e58770f-ae91-482a-b9c9-b51fa2692bf0.git
author: https://orcid.org/0000-0002-0012-7293
author: https://orcid.org/0000-0002-0934-4470
author: https://orcid.org/0000-0002-0170-6721
author: 0000-0002-1550-504X
keywords: Metamodel
keywords: Machine learning
keywords: SWMM
keywords: Graph neural networks
keywords: Surrogate model
keywords: GNN
keywords: Urban drainage systems
keywords: Time Series
programming language: Jupyter Notebook
programming language: Markdown
programming language: Other
programming language: Python
programming language: YAML
license:
  creative work: creativeWork
    name: MIT
reference publication: j.watres.2024.122396

https://orcid.org/0000-0002-0012-7293
type: Person
given name: Alexander
family name: Garzón
name: Alexander Garzón

https://orcid.org/0000-0002-0934-4470
type: Person
given name: Zoran
family name: Kapelan
name: Zoran Kapelan

https://orcid.org/0000-0002-0170-6721
type: Person
given name: Jeroen
family name: Langeveld
name: Jeroen Langeveld

0000-0002-1550-504X
type: Person
given name: Riccardo
family name: Taormina
name: Riccardo Taormina

j.watres.2024.122396
type: ScholarlyArticle
name: Transferable and data efficient metamodeling of storm water system nodal depths using auto-regressive graph neural networks
pagination: 122396
url: https://doi.org/10.1016%2Fj.watres.2024.122396