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Genetic algorithms assisted machine learning algorithms to optimize nano-phytoremediation of cadmium designed by response surface methodology.

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Title: Genetic algorithms assisted machine learning algorithms to optimize nano-phytoremediation of cadmium designed by response surface methodology.
Authors: Bas, Serpil1 (AUTHOR), Aasim, Muhammad2 (AUTHOR) mshazim@gmail.com, Gumus, Numan Emre3 (AUTHOR), Katırcı, Ramazan4 (AUTHOR), Ali, Seyid Amjad5 (AUTHOR), Karatas, Mehmet6 (AUTHOR)
Source: International Journal of Phytoremediation. 2025, Vol. 27 Issue 8, p1057-1065. 9p.
Database: Academic Search Ultimate
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  Data: Genetic algorithms assisted machine learning algorithms to optimize nano-phytoremediation of cadmium designed by response surface methodology.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Phytoremediation%22">International Journal of Phytoremediation</searchLink>. 2025, Vol. 27 Issue 8, p1057-1065. 9p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=185487721
RecordInfo BibRecord:
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        Value: 10.1080/15226514.2025.2473598
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      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 1057
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      – TitleFull: Genetic algorithms assisted machine learning algorithms to optimize nano-phytoremediation of cadmium designed by response surface methodology.
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            NameFull: Bas, Serpil
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            NameFull: Aasim, Muhammad
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            NameFull: Gumus, Numan Emre
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            NameFull: Katırcı, Ramazan
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            NameFull: Ali, Seyid Amjad
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              M: 06
              Text: 2025
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              Y: 2025
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