Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets

Abstract 0.76 1.78 of the dummy model). Furthermore, we demonstrate that it is possible to detect concept drift, i.e. situations where the model is applied outside its training domain and a new LES run may be necessary to obtain reliable results. Regression models can be used to replace LES simulations in estimating air pollutant concentrations, unless higher accuracy is needed. In order to have reliable results, it is however important to do the model and feature selection carefully to avoid overfitting and to use methods to detect the concept drift.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets ; volume:14 ; number:12 ; year:2021 ; pages:7411-7424 ; extent:14 ; Geoscientific model development ; 14, Heft 12 (2021), 7411-7424 (gesamt 14)

Classification and Topics

• Classification: Politik

Contributors, Places and Time

• Creator: Lange, Moritz ; Suominen, Henri ; Kurppa, Mona ; Järvi, Leena ; Oikarinen, Emilia ; Savvides, Rafael ; Puolamäki, Kai

Further information

• DOI: 10.5194/gmd-14-7411-2021
• URN: urn:nbn:de:101:1-2021120904342546602470
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:20 AM CEST