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- W2367724495 abstract "A glassy carbon electrode modified with dithiodiantipyrylmethane was prepared and used as a working electrode for the selective preconcentration of copper and lead in steel.The anodic stripping voltammetry for determination of copper and lead was studied in detail.The wavelet transform(WT),due to its ability of denoising,data compression and background correction,was used in the optimization of peak current signals selection,and the genetic algorithm(GA) was applied to optimize the structure and parameters of the BP artificial neural network(BP-ANN).Thus,over-fitting problems of BP-ANN were overcome by wavelet genetic neural network(WT-GA-BP-ANN).By comparison of the analytical results between two methods,it is showed that the WTGA-BP-ANN is better than WT-BP-ANN with the RSDs of 2.33%,3.49% for Cu2+ and 1.89%,3.77% for Pb2+,respectively." @default.
- W2367724495 created "2016-06-24" @default.
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- W2367724495 date "2006-01-01" @default.
- W2367724495 modified "2023-09-25" @default.
- W2367724495 title "Simultaneous determination of copper and lead in steel by wavelet genetic neural network-anodic stripping voltammetry" @default.
- W2367724495 hasPublicationYear "2006" @default.
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