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27671 |
Using remote sensing data for geological mapping in semi-arid environment: a machine learning approach
Enthalten in Earth science informatics Bd. 15, 3.2.2022, Nr. 1, date:3.2022: 485-496
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27672 |
Using remote sensing, process-based crop models, and machine learning to evaluate crop rotations across 20 million hectares in Western Australia
Enthalten in Agronomy for sustainable development Bd. 42, 12.12.2022, Nr. 6, date:12.2022: 1-14
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27673 |
Using sentinel-2 satellite images and machine learning algorithms to predict tropical pasture forage mass, crude protein, and fiber content
Enthalten in Scientific reports Bd. 14, 15.4.2024, Nr. 1, date:12.2024: 1-14
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27674 |
Using Smartphone Survey Data and Machine Learning to Identify Situational and Contextual Risk Factors for HIV Risk Behavior Among Men Who Have Sex with Men Who Are Not on PrEP
Enthalten in Prevention science Bd. 20, 9.5.2019, Nr. 6, date:8.2019: 904-913
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27675 |
Using spectral and temporal filters with EEG signal to predict the temporal lobe epilepsy outcome after antiseizure medication via machine learning
Enthalten in Scientific reports Bd. 13, 18.12.2023, Nr. 1, date:12.2023: 1-12
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27676 |
Using symbolic machine learning to assess and model substance transport and decay in water distribution networks
Enthalten in Scientific reports Bd. 14, 8.2.2024, Nr. 1, date:12.2024: 1-14
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27677 |
Using synthetic data to develop machine learning models to predict the performance of fiber-reinforced concrete
Enthalten in Asian journal of civil engineering Bd. 26, 11.3.2025, Nr. 5, date:5.2025: 2209-2221
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27678 |
Using the artificial bee colony technique to optimize machine learning algorithms in estimating the mature weight of camels
Enthalten in Tropical animal health and production Bd. 55, 17.2.2023, Nr. 2, date:4.2023: 1-10
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27679 |
Using the grouping function of machine learning algorithm to reduce the influence of information avoidance tendency during reading behavior
Enthalten in Smart Learning Environments Bd. 10, 27.11.2023, Nr. 1, date:12.2023: 1-16
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27680 |
Using the risk of spatial extrapolation by machine-learning models to assess the reliability of model predictions for conservation
Enthalten in Landscape ecology Bd. 38, 10.4.2023, Nr. 6, date:6.2023: 1363-1372
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