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Ergebnis der Suche nach: "Machine Learning"
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27391 - 27400 von 28841
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Artikel 27391 SPATIAL PREDICTION OF RECEIVED SIGNAL STRENGTH FOR CELLULAR COMMUNICATION USING SUPPORT VECTOR MACHINE AND K-NEAREST NEIGHBOURS REGRESSION
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-4/W9-2024, 2024: 291-297. 7 S.
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Artikel 27392 Spatial prediction of soil contamination based on machine learning: a review
Enthalten in Frontiers of environmental science & engineering Bd. 17, 17.2.2023, Nr. 8, date:8.2023: 1-17
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Artikel 27393 Spatial prediction of soil micronutrients using machine learning algorithms integrated with multiple digital covariates
Enthalten in Nutrient cycling in agroecosystems Bd. 127, 13.8.2023, Nr. 1, date:9.2023: 137-153
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Artikel 27394 Spatial prediction of soil organic carbon stocks in an arid rangeland using machine learning algorithms
Enthalten in Environmental monitoring and assessment Bd. 193, 17.11.2021, Nr. 12, date:12.2021: 1-17
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Artikel 27395 Spatial predictions of groundwater potential using automated machine learning (AutoML): a comparative study of feature selection and training sample size in Qinghai Province, China
Enthalten in Environmental science and pollution research Bd. 31, 1.12.2023, Nr. 1, date:1.2024: 1127-1145
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Artikel 27396 Spatial recognition and semi-quantification of epigenetic events in pancreatic cancer subtypes with multiplexed molecular imaging and machine learning
Enthalten in Scientific reports Bd. 15, 22.2.2025, Nr. 1, date:12.2025: 1-17
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Artikel 27397 Spatial statistical machine learning models to assess the relationship between development vulnerabilities and educational factors in children in Queensland, Australia
Enthalten in BMC public health Bd. 22, 30.11.2022, Nr. 1, date:12.2022: 1-12
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Artikel 27398 Spatial temperature prediction—a machine learning and GIS perspective
Enthalten in Theoretical and applied climatology Bd. 155, 7.10.2024, Nr. 11, date:11.2024: 9619-9642
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Artikel 27399 SPATIALLY AWARE LANDSLIDE SUSCEPTIBILITY PREDICTION USING A GEOGRAPHICAL RANDOM FOREST APPROACH
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-4/W9-2024, 2024: 363-370. 8 S.
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Artikel 27400 Spatio-temporal based video anomaly detection using deep neural networks
Enthalten in International journal of information technology Bd. 15, 7.3.2023, Nr. 3, date:3.2023: 1569-1581
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