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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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-025-86550-6 |
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