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首页> 外文期刊>Spectrochimica acta, Part A. Molecular and biomolecular spectroscopy >Application of principle component analysis-artificial neural network for simultaneous determination of zirconium and hafnium in real samples
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Application of principle component analysis-artificial neural network for simultaneous determination of zirconium and hafnium in real samples

机译:主成分分析-人工神经网络同时测定真实样品中锆和and的应用

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摘要

Determination of zirconium and hafnium were done by applying singular value decomposition and a feed forward Neural Network Algorithm with back propagation of error. The determination of trace amounts of mixtures of Zr(IV) and Hf(IV) in various matrices (river, lap and industrial wastewater) were investigated by PC-ANN using the complexes formed between Alizarin Red S, Zr and HE The results showed that measurement is possible in the ranges of 0.03-3.4 and 0.2-7.0 mu g ml(-1) for Zr(IV) and Hf(IV), respectively. The detection limits were 0.02 and 0.08 mu Lg ml(-1) for Zr(IV) and Hf(IV), respectively. The results also show very good agreement between true and predicted concentration values and have the ability to use in routine analysis. (c) 2005 Elsevier B.V. All rights reserved.
机译:锆和ha的测定是通过奇异值分解和前向神经网络算法进行的,误差反向传播。 PC-ANN使用茜素红S,Zr和HE形成的配合物,通过PC-ANN研究了各种基质(河流,膝部废水和工业废水)中痕量Zr(IV)和Hf(IV)混合物的测定结果表明: Zr(IV)和Hf(IV)的测量范围分别为0.03-3.4和0.2-7.0μg ml(-1)。 Zr(IV)和Hf(IV)的检出限分别为0.02和0.08μLg ml(-1)。结果还显示真实浓度值和预测浓度值之间有很好的一致性,并且可以在常规分析中使用。 (c)2005 Elsevier B.V.保留所有权利。

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