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一种用于电感耦合等离子体原子发射光谱定性分析的遗传算法方法

[A genetic algorithm approach to qualitative analysis in inductively coupled plasma-atomic emission spectroscopy].

作者信息

Peng Bin, Liu Ke-ling, Li Zhi-min, Wang Yue-song, Huang Tu-jiang

机构信息

Institute of Chemical Metallurgy, Chinese Academy of Sciences, Beijing 100080, China.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2002 Jun;22(3):458-60.

Abstract

Genetic algorithm (GA) is used in automatic qualitative analysis by a sequential inductively coupled plasma spectrometer (ICP-AES) and a computer program is developed in this paper. No any standard samples are needed, and spectroscopic interferences can be eliminated. All elements and their concentration ranges of an unknown sample can be reported. The replication rate Pr, crossover rate Pc, and mutation rate of the genetic algorithm were adjusted to be 0.6, 0.4 and 0 respectively. The analytical results of GA are in good agreement with the reference values. It indicates that, combined with the intensity information, the GA can be applied to spectroscopic qualitative analysis and expected to become an effective method in qualitative analysis in ICP-AES after further work.

摘要

本文将遗传算法(GA)应用于顺序电感耦合等离子体光谱仪(ICP-AES)的自动定性分析,并开发了相应的计算机程序。该方法无需任何标准样品,能够消除光谱干扰,可报告未知样品中所有元素及其浓度范围。遗传算法的复制率Pr、交叉率Pc和变异率分别调整为0.6、0.4和0。GA的分析结果与参考值吻合良好。结果表明,结合强度信息,GA可用于光谱定性分析,经过进一步研究有望成为ICP-AES定性分析的有效方法。

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