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25921 |
Predicting the Soft Error Vulnerability of Parallel Applications Using Machine Learning
Enthalten in International journal of parallel programming Bd. 49, 28.3.2021, Nr. 3, date:6.2021: 410-439
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25922 |
Predicting the spatial distribution of stable isotopes in precipitation using a machine learning approach: a comparative assessment of random forest variants
Enthalten in GEM Bd. 14, 12.6.2023, Nr. 1, date:12.2023: 1-19
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25923 |
Predicting the Stability of Rock Slopes in the Presence of Diverse Joint Networks and External Factors Using Machine Learning Algorithms
Enthalten in Mining, metallurgy & exploration Bd. 41, 19.8.2024, Nr. 5, date:10.2024: 2421-2440
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25924 |
Predicting the stereoselectivity of chemical reactions by composite machine learning method
Enthalten in Scientific reports Bd. 14, 27.5.2024, Nr. 1, date:12.2024: 1-12
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25925 |
Predicting the strength of alkali-activated masonry blocks using machine learning models: geopolymer mortar with quarry waste, rice husk ash, and eggshell ash
Enthalten in Journal of building pathology and rehabilitation Bd. 10, 28.1.2025, Nr. 1, date:6.2025: 1-25
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25926 |
Predicting the success of startups using a machine learning approach
Enthalten in Journal of innovation and entrepreneurship Bd. 13, 28.10.2024, Nr. 1, date:12.2024: 1-27
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25927 |
Predicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP
Enthalten in BMC genomics Bd. 23, 7.1.2022, Nr. 1, date:12.2022: 1-18
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25928 |
Predicting the time to get back to work using statistical models and machine learning approaches
Enthalten in BMC medical research methodology Bd. 24, 29.11.2024, Nr. 1, date:12.2024: 1-8
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25929 |
Predicting the ultimate tensile strength of AISI 1045 steel and 2017-T4 aluminum alloy joints in a laser-assisted rotary friction welding process using machine learning: a comparison with response surface methodology
Enthalten in The international journal of advanced manufacturing technology Bd. 116, 30.6.2021, Nr. 3-4, date:9.2021: 1247-1257
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25930 |
Predicting the value of football players: machine learning techniques and sensitivity analysis based on FIFA and real-world statistical datasets
Enthalten in Applied intelligence Bd. 55, 4.1.2025, Nr. 4, date:2.2025: 1-26
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