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Evaluating the efficacy of PCA and t-SNE in optimizing input features for groundwater level simulation using machine learning models.

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Title: Evaluating the efficacy of PCA and t-SNE in optimizing input features for groundwater level simulation using machine learning models.
Authors: Wang, Nan1, nancyccitccit@sina.com, Zhou, Qiang2, Gao, Jinhua1, Wang, Zi'xi3
Source: Environmental Earth Sciences; Jun2025, Vol. 84 Issue 12, p1-21, 21p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Evaluating the efficacy of PCA and t-SNE in optimizing input features for groundwater level simulation using machine learning models.
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  Data: <searchLink fieldCode="AU" term="%22Wang%2C+Nan%22">Wang, Nan</searchLink><relatesTo>1</relatesTo>, <i>nancyccitccit@sina.com</i><br /><searchLink fieldCode="AU" term="%22Zhou%2C+Qiang%22">Zhou, Qiang</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Gao%2C+Jinhua%22">Gao, Jinhua</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Wang%2C+Zi'xi%22">Wang, Zi'xi</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Earth+Sciences%22">Environmental Earth Sciences</searchLink>; Jun2025, Vol. 84 Issue 12, p1-21, 21p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=186489133
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      – Type: doi
        Value: 10.1007/s12665-025-12357-3
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      – Code: eng
        Text: English
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      – TitleFull: Evaluating the efficacy of PCA and t-SNE in optimizing input features for groundwater level simulation using machine learning models.
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            NameFull: Zhou, Qiang
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              Text: Jun2025
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              Y: 2025
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              Value: 84
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