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Ergebnis der Suche nach: "Machine Learning"
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Artikel 781 Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 14: 3305-3326. 22 S.
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Artikel 782 To what extent do flood-inducing storm events change future flood hazards?
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 14: 3161-3190. 30 S.
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Artikel 783 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.
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Artikel 784 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.
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Artikel 785 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.
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Artikel 786 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.
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Artikel 787 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.
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Artikel 788 Toward interpretable LSTM-based modeling of hydrological systems
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 4: 945-971. 27 S.
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Artikel 789 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.
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Artikel 790 Accelerating NMR Shielding Calculations Through Machine Learning Methods: Application to Magnesium Sodium Silicate Glasses
Enthalten in ChemPhysChem Bd. 25, 2024, Nr. 22. 13 S.
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