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"Machine Learning"
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361
Estimating surface sulfur dioxide concentrations from satellite data over eastern China: Using chemical transport models vs. machine learning
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 20: 13527-13545. 19 S.
362
Aerosol type classification with machine learning techniques applied to multiwavelength lidar data from EARLINET
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 19: 12549-12567. 19 S.
363
Global ionospheric sporadic <italic>E</italic> intensity prediction from GNSS RO using a novel stacking machine learning method incorporated with physical observations
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 18: 11517-11534. 18 S.
364
A machine-learning-based perspective on deep convective clouds and their organisation in 3D – Part 2: Spatial–temporal patterns of convective organisation
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 18: 10797-10822. 26 S.
365
A machine-learning-based perspective on deep convective clouds and their organisation in 3D – Part 1: Influence of deep convective cores on the cloud life cycle
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 18: 10773-10795. 23 S.
366
Dust pollution substantially weakens the impact of ammonia emission reduction on particulate nitrate formation
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 18: 10587-10601. 15 S.
367
Impact of topographic wind conditions on dust particle size distribution: insights from a regional dust reanalysis dataset
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 17: 9583-9600. 18 S.
368
Explainable ensemble machine learning revealing spatiotemporal heterogeneity in driving factors of particulate nitro-aromatic compounds in eastern China
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 15: 8407-8425. 19 S.
369
Tropospheric ozone trends and attributions over East and Southeast Asia in 1995–2019: an integrated assessment using statistical methods, machine learning models, and multiple chemical transport models
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 14: 7991-8028. 38 S.
370
Machine-learning-assisted chemical characterization and optical properties of atmospheric brown carbon in Nanjing, China
Enthalten in Atmospheric chemistry and physics Bd. 25, 2025, Nr. 14: 7619-7645. 27 S.
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