Radix Notoginseng Quality Assessment Based on Rough Sets and Neutral Network

Abstract

To discriminate the quality on traditional Chinese medicines RADIX NOTOGINSENG real-time, according to the characters of radix notoginseng 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 artificial neutral network, its generalization is well. Using methods rough sets and artificial neutral network to assess radix notoginseng 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.