Grey relational analysis and LS-SVM modeling for the fingerprint-efficacy study of Yinhuang granules

被引:0
|
作者
Li, Ke [1 ]
Gao, Yan [2 ]
Wang, Bianli [2 ]
Lv, Ling [2 ]
Zhao, Bonian [2 ]
Zhao, Hongpeng [3 ]
机构
[1] Shandong Acad Sci, Inst Automat, Jinan, Peoples R China
[2] Shandong Acad Chinese Med, Shandong Key Lab Chinese Med Qual Stand Res, Jinan, Peoples R China
[3] Qianfo Mt Hosp Shandong Prov, Jinan, Peoples R China
基金
中国国家自然科学基金;
关键词
anti-respiratory syncytial virus; grey relational analysis; least squares support vector machines; Yinhuang granule;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, the grey relational analysis method was used to identify the key constituents of Yinhuang granules according to the anti-respiratory syncytial virus activities in drug serum by in vitro laboratory experiments. Furthermore, a model that characterizes the relationship between constituents and median effective concentrations was established through the least squares support vector machine (LS-SVM) regression technique. The computational simulation showed that this model fitted well with the experimental data, and validation experimental results also supported the theoretical predictions.
引用
收藏
页码:344 / 349
页数:6
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