Grey relational analysis and LS-SVM modeling for the fingerprint-efficacy study of Yinhuang granules
| Autor: | Bianli Wang, Ling Lv, Bonian Zhao, Ke Li, Yan Gao, Hongpeng Zhao |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
business.industry 010401 analytical chemistry Experimental data Pattern recognition 02 engineering and technology Fingerprint recognition computer.software_genre 01 natural sciences Grey relational analysis Regression 0104 chemical sciences Data modeling Support vector machine 020901 industrial engineering & automation Fingerprint Least squares support vector machine Artificial intelligence Data mining business computer Mathematics |
| Zdroj: | 2016 International Conference on Advanced Mechatronic Systems (ICAMechS). |
| DOI: | 10.1109/icamechs.2016.7813472 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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