|
26481 |
Spatial prediction of flood susceptible areas using machine learning methods in the Siahkhor Watershed of Kermanshah province Enthalten in Earth science informatics Bd. 18, 10.12.2024, Nr. 1, date:1.2025: 1-13
|
|
|
26482 |
Spatial prediction of forest fires in India: a machine learning approach for improved risk assessment and early warning systems Enthalten in Environmental science and pollution research Bd. 32, 1.2.2025, Nr. 8, date:2.2025: 4856-4878
|
|
|
26483 |
Spatial prediction of groundwater levels using machine learning and geostatistical models: a case study of coastal faulted aquifer systems in southeastern Tunisia Enthalten in Hydrogeology journal Bd. 31, 22.8.2023, Nr. 6, date:9.2023: 1387-1404
|
|
|
26484 |
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.
|
|
|
26485 |
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
|
|
|
26486 |
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
|
|
|
26487 |
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
|
|
|
26488 |
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
|
|
|
26489 |
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
|
|
|
26490 |
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
|
|