Katalog der Deutschen Nationalbibliothek

Ergebnis der Suche nach: "Machine Learning"
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	791	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.
	792	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.
	793	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.
	794	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.
	795	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.
	796	Toward interpretable LSTM-based modeling of hydrological systems Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 4: 945-971. 27 S.
	797	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.
	798	Accelerating NMR Shielding Calculations Through Machine Learning Methods: Application to Magnesium Sodium Silicate Glasses Enthalten in ChemPhysChem Bd. 25, 2024, Nr. 22. 13 S.
	799	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.
	800	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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