Grey relational analysis and LS-SVM modeling for the fingerprint-efficacy study of Yinhuang granules
- Resource Type
- Conference
- Authors
- Li, Ke; Gao, Yan; Wang, Bianli; Lv, Ling; Zhao, Bonian; Zhao, Hongpeng
- Source
- 2016 International Conference on Advanced Mechatronic Systems (ICAMechS) Advanced Mechatronic Systems (ICAMechS), 2016 International Conference on. :344-349 Nov, 2016
- Subject
- Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Fingerprint recognition
Data models
Drugs
Standards
Support vector machines
Kernel
In vitro
anti-respiratory syncytial virus
grey relational analysis
least squares support vector machines
Yinhuang granule
- Language
- ISSN
- 2325-0690
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.