高等学校化学学报

高等学校化学学报 ›› 2002, Vol. 23 ›› Issue (7): 1269.

• 研究论文 • 上一篇    下一篇

一种基于免疫算法的新型因子分析算法

邵学广, 李梅青, 邵利民   

  1. 中国科学技术大学化学系, 合肥 230026
  • 收稿日期:2001-05-09 出版日期:2002-07-24 发布日期:2002-07-24
  • 通讯作者: 邵学广(1963年出生),男,博士,教授,博士生导师,从事化学计量学研究.
  • 基金资助:

    国家自然科学基金(批准号:29975027)

A Novel Algorithm for Chemical Factor Analysis Based on Immune Algorithm

SHAO Xue-Guang, LI Mei-Qing, SHAO Li-Min   

  1. Department of Chemistry, University of Science and Technology of China, Hefei 230026, China
  • Received:2001-05-09 Online:2002-07-24 Published:2002-07-24

PDF (PC)

被引次数

14

摘要： 基于免疫算法的基本思想,提出了新的免疫主成分分析法(IPCA),该方法将免疫算法中抗体对抗原的消除运算应用于二维数据矩阵的正交分解,可得到矩阵的特征值和特征向量.结果表明,IPCA与传统的主成分分析法比较,对HPLC-DAD模拟信号的计算结果基本一致.对HPLC-DAD实验信号的解析结果表明,将IPCA与窗口因子分析技术结合比传统的WFA具有更强的解析能力.

关键词: 免疫算法, 主成分分析, 因子分析, 重叠信号解析

Abstract: Based on the principal of immune algorithm, a novel algorithm for chemical factor analysis was proposed, and called immune principal component analysis(IPCA). The basic idea of the proposed method is that it takes a data matrix as antigen, the retrieving eigen vector as antibody, and the orthogonal decomposition of the matrix can be achieved by an iteration of subtracting the principal component represented by the eigen vector, simulating the process of the interaction between antibody and antigen in an immune system. Comparing with the conventional principal component analysis, similar results were obtained. But if we combine the IPCAalgorithm with window factor analysis(WFA) technique, it will be more suitable for resolution of overlapping HPLC-DADsignals than the conventional WFAtechnique. Both simulated and experimental data sets were investigated. Similar results are obtained by the IPCAand PCAfor principal component analysis, but the IPCA-WFAis superior to the conventional WFAin resolution of the multicomponent overlapping HPLC-DADsignals.

Key words: Immune algorithm, Principal component analysis, Factor analysis, Resolution of overlapping signal

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