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• W3160972328 abstract "Abstract In the context of kernel nonparametric regression, the curve estimation is fully depending on the smoothing parameter. At this point, the nature-inspired algorithms can be used as an alternative tool to find the optimal selection. In this paper, a bat optimization algorithm method is proposed to choose the smoothing parameter in Nadaraya-Watson kernel nonparametric regression. The proposed method will efficiently help to find the best smoothing parameter with a high prediction. The proposed method is compared with four famous ` of prediction capability." @default.
• W3160972328 created "2021-05-24" @default.
• W3160972328 creator A5032449312 @default.
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• W3160972328 date "2021-05-01" @default.
• W3160972328 modified "2023-10-16" @default.
• W3160972328 title "Smoothing parameter selection in kernel nonparametric regression using bat optimization algorithm" @default.
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• W3160972328 doi "https://doi.org/10.1088/1742-6596/1897/1/012010" @default.
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