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Comparison of extreme gradient boosting, deep learning, and self-organizing map methods in predicting groundwater depth.

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Title: Comparison of extreme gradient boosting, deep learning, and self-organizing map methods in predicting groundwater depth.
Authors: Gholami, Vahid1, Gholami.vahid@gmail.com, Khaleghi, Mohammad Reza2, drmrkhaleghi@gmail.com, Salimi, Edris Taghvaye3, Edristaghvaei@yahoo.com
Source: Environmental Earth Sciences; Apr2025, Vol. 84 Issue 7, p1-12, 12p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 184915637
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PubType: Academic Journal
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  Data: Comparison of extreme gradient boosting, deep learning, and self-organizing map methods in predicting groundwater depth.
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Earth+Sciences%22">Environmental Earth Sciences</searchLink>; Apr2025, Vol. 84 Issue 7, p1-12, 12p
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      – Type: doi
        Value: 10.1007/s12665-025-12183-7
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      – Code: eng
        Text: English
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        PageCount: 12
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      – TitleFull: Comparison of extreme gradient boosting, deep learning, and self-organizing map methods in predicting groundwater depth.
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            NameFull: Gholami, Vahid
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            NameFull: Khaleghi, Mohammad Reza
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            NameFull: Salimi, Edris Taghvaye
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              Text: Apr2025
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              Y: 2025
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              Value: 84
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              Value: 7
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