Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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	781	When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 13: 3051-3077. 27 S.
	782	Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 11: 2531-2553. 23 S.
	783	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.
	784	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.
	785	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.
	786	Toward interpretable LSTM-based modeling of hydrological systems Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 4: 945-971. 27 S.
	787	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.
	788	Accelerating NMR Shielding Calculations Through Machine Learning Methods: Application to Magnesium Sodium Silicate Glasses Enthalten in ChemPhysChem Bd. 25, 2024, Nr. 22. 13 S.
	789	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.
	790	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.

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