The Application of Multiobjective Genetic Algorithm to the Parameter Optimization of Single-Well Potential Stochastic Resonance Algorithm Aimed at Simultaneous Determination of Multiple Weak Chromatographic Peaks

被引:0
作者
Deng, Haishan [1 ]
Xie, Shaofei [2 ]
Xiang, Bingren [3 ]
Zhan, Ying [4 ]
Li, Wei [1 ]
Li, Xiaohua [5 ]
Jiang, Caiyun [5 ]
Wu, Xiaohong [5 ]
Liu, Dan [1 ]
机构
[1] Nanjing Univ Chinese Med, Coll Pharm, Dept Pharm, Nanjing 210023, Jiangsu, Peoples R China
[2] Nanjing Changao Pharmaceut Technol Ltd, Nanjing 210038, Jiangsu, Peoples R China
[3] China Pharmaceut Univ, Ctr Instrumental Anal, Nanjing 210009, Jiangsu, Peoples R China
[4] Southeast Univ, Zhongda Hosp, Nanjing 210009, Jiangsu, Peoples R China
[5] Jiangsu Inst Econ & Trade Technol, Dept Engn & Technol, Nanjing 210007, Jiangsu, Peoples R China
来源
SCIENTIFIC WORLD JOURNAL | 2014年
基金
中国国家自然科学基金;
关键词
QUANTITATIVE-ANALYSIS; LIQUID-CHROMATOGRAPHY; MASS-SPECTROMETRY; TRACE ANALYSIS; SIGNAL; PLASMA; WATER; CHEMOMETRICS;
D O I
10.1155/2014/767018
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Simultaneous determination of multiple weak chromatographic peaks via stochastic resonance algorithm attracts much attention in recent years. However, the optimization of the parameters is complicated and time consuming, although the single-well potential stochastic resonance algorithm (SSRA) has already reduced the number of parameters to only one and simplified the process significantly. Even worse, it is often difficult to keep amplified peaks with beautiful peak shape. Therefore, multiobjective genetic algorithm was employed to optimize the parameter of SSRA for multiple optimization objectives (i.e., S/N and peak shape) and multiple chromatographic peaks. The applicability of the proposed method was evaluated with an experimental data set of Sudan dyes, and the results showed an excellent quantitative relationship between different concentrations and responses.
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页数:6
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