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Ergebnis der Suche nach: "Machine Learning"
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Artikel 761 Metamorphic testing of machine learning and conceptual hydrologic models
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 11: 2505-2529. 25 S.
Online Ressource
Artikel 762 Towards understanding the influence of seasons on low-groundwater periods based on explainable machine learning
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 9: 2167-2178. 12 S.
Online Ressource
Artikel 763 Disentangling coastal groundwater level dynamics in a global dataset
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 5: 1215-1249. 35 S.
Online Ressource
Artikel 764 Toward interpretable LSTM-based modeling of hydrological systems
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 4: 945-971. 27 S.
Online Ressource
Artikel 765 A comprehensive study of deep learning for soil moisture prediction
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 4: 917-943. 27 S.
Online Ressource
Artikel 766 Accelerating NMR Shielding Calculations Through Machine Learning Methods: Application to Magnesium Sodium Silicate Glasses
Enthalten in ChemPhysChem Bd. 25, 2024, Nr. 22. 13 S.
Online Ressource
Artikel 767 Improving the predictions of black carbon (BC) optical properties at various aging stages using a machine-learning-based approach
Enthalten in Atmospheric chemistry and physics Bd. 24, 2024, Nr. 15: 8821-8846. 26 S.
Online Ressource
Artikel 768 Enhancing long-term trend simulation of the global tropospheric hydroxyl (TOH) and its drivers from 2005 to 2019: a synergistic integration of model simulations and satellite observations
Enthalten in Atmospheric chemistry and physics Bd. 24, 2024, Nr. 15: 8677-8701. 25 S.
Online Ressource
Artikel 769 Identifying decadal trends in deweathered concentrations of criteria air pollutants in Canadian urban atmospheres with machine learning approaches
Enthalten in Atmospheric chemistry and physics Bd. 24, 2024, Nr. 13: 7773-7791. 19 S.
Online Ressource
Artikel 770 Secondary organic aerosols derived from intermediate-volatility n-alkanes adopt low-viscous phase state
Enthalten in Atmospheric chemistry and physics Bd. 24, 2024, Nr. 9: 5549-5565. 17 S.
Online Ressource


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