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化学学报
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化学学报 ›› 1997, Vol. 55 ›› Issue (7): 693-702. 上一篇    下一篇

研究论文

用遗传算法优化的约束背景双线性化方法处理含未知背景组分干扰的色谱二维谱图体系

陈文灿;崔卉;陈增萍;许静;莫文莉;梁逸曾   

  1. 湖南大学化学化工系;湖南大学计量学和化学传感技术研究所
  • 发布日期:1997-07-15

Numeric genetic algorithm applying in constrained background bilinearization for two-way chromatography

CHEN WENCAN;CUI HUI;CHEN ZENGPING;XU JING;MO WENLI;LIANG YIZENG   

  • Published:1997-07-15

PDF

432

被引次数

36 | 5

数值遗传算法是全局优化方法, 本文将其引入约束背景双线性化问题的优化求解过程, 以避免陷入局部最优。用本方法处理了模拟数据和两个实际含未知背景干扰的色谱二维谱图体系, 并探讨了如何提高遗传算法在优化平台区域的寻优速度,结果令人满意。

关键词: 色谱, 遗传算法, 约束背景双线性化, 二维谱图, 数据模拟

Numeric genetic algorithm (NGA) is an optimization technique for locating the global optimun. In this paper NGA was used as the optimization procedure in the constrained background bilinearization (CBBL) of two-way bilinear data in order to reduced the possibility of sinking into local optima. The behavior of the algorithm was studied by simulations and real two-way chromatographic data. The results show that, with this algorithm, correct concentrations of the mixture can be determined in the presence of unknown interference. Some details in NGA are also discussed.

Key words: CHROMATOGRAPHY

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