Transferable and data efficient metamodeling of storm water system nodal depths using auto-regressive graph neural networks

Alexander Garzón^*, Zoran Kapelan, Jeroen Langeveld, Riccardo Taormina

^*Corresponding author for this work

Sanitary Engineering

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SWMM GNN metamodel – Code for paper: Transferable and Data Efficient Metamodeling of Storm Water System Nodal Depths Using Auto-Regressive Graph Neural Networks
Garzón Díaz, J. A. (Creator), Kapelan, Z. (Creator), Langeveld, J. G. (Creator) & Taormina, R. (Creator), TU Delft - 4TU.ResearchData, 2024
DOI: 10.4121/989A0D3D-3B4D-47C7-8677-31C5975F9DEC
Dataset/Software: Software
Data for paper "Transferable and Data Efficient Metamodeling of Storm Water System Nodal Depths Using Auto-Regressive Graph Neural Networks"
Garzón Díaz, J. A. (Creator), Kapelan, Z. (Creator), Langeveld, J. G. (Creator) & Taormina, R. (Creator), TU Delft - 4TU.ResearchData, 12 Sept 2024
DOI: 10.4121/FEC1E3DE-9586-4A61-B3A1-02382592E52C
Dataset/Software: Dataset