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[基于人工神经网络和紫外光谱法测定锌、铜和钴含量的研究]

[Study on the determination of contents of Zn, Cu and Co by using artifical neural network and ultraviolet spectrum].

作者信息

Yan Z, Jiang X, Zhang S

机构信息

Department of Analytical Chemistry, China Pharmaceutical University, 210009 Nanjing.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2000 Jun;20(3):409-11.

Abstract

By means of artificial neural network and back-propagation train algorithm, the three-component metal coordinate compounds of PAR-Zn, Cu, Co were determined simultaneously, in which the spectra overlapped. In 580-440 nm, the absorbance(A) at 14 wavelength were taken as character parameter of artificial neural network, and samples were arranged by method of uniformity design. The mean recovery of Zn, Cu, Co were 95.22%, 95.98% and 100.5%. The experiment results show that the determination is accurate, and the method has good performance.

摘要

通过人工神经网络和反向传播训练算法,同时测定了PAR与锌、铜、钴形成的三组分金属配位化合物,其中光谱相互重叠。在580 - 440 nm范围内,选取14个波长处的吸光度(A)作为人工神经网络的特征参数,并采用均匀设计法安排样品。锌、铜、钴的平均回收率分别为95.22%、95.98%和100.5%。实验结果表明测定准确,该方法性能良好。

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