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26001 |
Prediction of creep degradation in Fe-Cr-Ni single-crystal alloys for high-temperature applications: a molecular-dynamics and machine-learning approach
Enthalten in Mechanics of time-dependent materials Bd. 29, 11.12.2024, Nr. 1, date:3.2025: 1-20
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26002 |
Prediction of creep properties of Co–10Al–9W superalloys with machine learning
Enthalten in Journal of materials science Bd. 59, 13.3.2024, Nr. 11, date:3.2024: 4571-4585
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26003 |
Prediction of cross-sectional features of SPR joints based on the punch force-displacement curve using machine learning
Enthalten in The international journal of advanced manufacturing technology Bd. 128, 25.8.2023, Nr. 9-10, date:10.2023: 4023-4034
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26004 |
Prediction of cytochrome P450-mediated bioactivation using machine learning models and in vitro validation
Enthalten in Archives of toxicology Bd. 98, 16.3.2024, Nr. 5, date:5.2024: 1457-1467
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26005 |
Prediction of daily sea water temperature in Turkish seas using machine learning approaches
Enthalten in Arabian journal of geosciences Bd. 15, 19.10.2022, Nr. 21, date:11.2022: 1-19
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26006 |
Prediction of damage potential in mainshock–aftershock sequences using machine learning algorithms
Enthalten in Earthquake engineering and engineering vibration Bd. 23, 8.10.2024, Nr. 4, date:10.2024: 919-938
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26007 |
PREDICTION OF DEFORMATION CAUSED BY LANDSLIDES BASED ON GRAPH CONVOLUTION NETWORKS ALGORITHM AND DINSAR TECHNIQUE
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-4/W1-2022, 2023: 391-397. 7 S.
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26008 |
Prediction of delayed graft function after kidney transplantation: comparison between logistic regression and machine learning methods
Enthalten in BMC medical informatics and decision making Bd. 15, 14.10.2015, Nr. 1, date:12.2015: 1-10
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26009 |
Prediction of dengue outbreak in Selangor Malaysia using machine learning techniques
Enthalten in Scientific reports Bd. 11, 13.1.2021, Nr. 1, date:12.2021: 1-9
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26010 |
Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China
Enthalten in Journal of health, population and nutrition Bd. 44, 4.6.2025, Nr. 1, date:12.2025: 1-15
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