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Autor:
Roland Löwe, Matthias Kjær Adamsen, Phillip Aarestrup, Franca Bauer, Allan Peter Engsig-Karup, Morten Grum, Frederik Tinus Jeppesen, Peter Steen Mikkelsen
In this work we illustrate how scientific machine learning algorithms (SciML) can be used to facilitate the development of digital twins for urban drainage systems. Scientific machine learning integrates classical, modelling techniques from scientifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c679d64472ac5a0fad89f03e03305843
https://doi.org/10.5194/egusphere-egu23-5672
https://doi.org/10.5194/egusphere-egu23-5672