Exploration of transfer learning techniques for the prediction of PM10

Abstract Modelling of pollutants provides valuable insights into air quality dynamics, aiding exposure assessment where direct measurements are not viable. Machine learning (ML) models can be employed to explore such dynamics, including the prediction of air pollution concentrations, yet demanding e...

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Bibliographic Details
Main Authors: Michael Poelzl, Roman Kern, Simonas Kecorius, Mario Lovrić
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-86550-6
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