Implementation of random forest, adaptive boosting, and gradient boosting decision trees algorithms for gully erosion susceptibility mapping using remote sensing and GIS.

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Title: Implementation of random forest, adaptive boosting, and gradient boosting decision trees algorithms for gully erosion susceptibility mapping using remote sensing and GIS.
Authors: Ait Naceur, Hassan1,2, Abdo, Hazem Ghassan2, hazemabdo@tartous-univ.edu.sy, Igmoullan, Brahim1, Namous, Mustapha3, Alshehri, Fahad2, A Albanai, Jasem4
Source: Environmental Earth Sciences; Feb2024, Vol. 83 Issue 3, p1-20, 20p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 175846695
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  Data: Implementation of random forest, adaptive boosting, and gradient boosting decision trees algorithms for gully erosion susceptibility mapping using remote sensing and GIS.
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Earth+Sciences%22">Environmental Earth Sciences</searchLink>; Feb2024, Vol. 83 Issue 3, p1-20, 20p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=175846695
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      – Type: doi
        Value: 10.1007/s12665-024-11424-5
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      – Code: eng
        Text: English
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      – TitleFull: Implementation of random forest, adaptive boosting, and gradient boosting decision trees algorithms for gully erosion susceptibility mapping using remote sensing and GIS.
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            NameFull: Abdo, Hazem Ghassan
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              Text: Feb2024
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              Y: 2024
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