Eucommia Bark Quality Assessment Based on Rough Sets and Perceptron
Tie Wang, Zhiguang Chen, Gaonan Wang, Jianyang Lin · 2008
To discriminate the quality on traditional Chinese medicines Eucommia Bark real-time, according to the characters of Eucommia Bark finger printer, the basic concepts of rough set are introduced briefly. For rough sets can only deal with discrete data, the discretization of data is the key factor in the rough sets applied in quality assessment, we present a method of discretization based on cluster category which combined with the characteristic of rough sets and perceptron, its generalization is well. Using methods rough sets and artificial neutral network to assess Eucommia Bark without any additional prior model assumption, rough sets data analysis can eliminate the redundancy of attributes and its value, identify the dependence in the attributes. We get a collective production rules about the chemical pattern classification system from sample data. When the model of chemical pattern classification is built by these rules, its meaning is very understandable in chemical domain, and the prediction of the model is also well.