| 人工神经网络用于紫外光谱同时测定Zn、Cu、Co含量的研究 |
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| 引用本文： | 严拯宇,姜新民,张圣华.人工神经网络用于紫外光谱同时测定Zn、Cu、Co含量的研究[J].光谱学与光谱分析,2000,20(3):409-411. |
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| 作者姓名： | 严拯宇 姜新民 张圣华 |
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| 作者单位： | 中国药科大学分析化学教研室,210009,南京 |
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| 摘 要： | 本文采用ＰＡＲ－Ｚｎ、Ｃｕ、Ｃｏ显色体系，应用人工神经网络原理，通过误差反向传播方法，对于紫外吸收重叠的三组分金属配合物体系同时进行含量测定。在５８０￣４４０ｎｍ的范围内，以１４个特定波长处的吸收值作为网络特征参数，并通过均匀设计安排样本。Ｚｎ、Ｃｕ、Ｃｏ三者的平均回收率分别为９５．２２％、９５．９８％、１００．５％。实验表明，其结果准确，性能良好。
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| 关 键 词： | 人工神经网络 紫外光谱 锌 铜 钴 三组分配合物 |
Study on the Determination of Contents of Zn,Cu and Co by Using Artificial Nerual Network and Ultraviolet Spectrum |
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| Zhengyu YAN,Xinmin JIANG,Shenghua ZHANG.Study on the Determination of Contents of Zn,Cu and Co by Using Artificial Nerual Network and Ultraviolet Spectrum[J].Spectroscopy and Spectral Analysis,2000,20(3):409-411. |
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| Authors: | Zhengyu YAN Xinmin JIANG Shenghua ZHANG |
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| Institution: | Department of Analytical Chemistry, China Pharmaceutical University, 210009 Nanjing. |
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| 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. |
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| Keywords: | Artificial neural network Coordinate compound Ultraviolet spectrum Zinc Copper Chromiun |
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