To solve the problem of fast identifying the quality sort of chinese traditional medicine products with nonlinear and fuzzy edges of the quality sort, a new method combining near infrared spectroscopy (NIRS) with fuzzy neural network was proposed. The method can differentiate the pattern classification of NIRS of chinese traditional medicine products with complex chemical components, resulting in fast evaluating product quality. An example of distinguishing the manufacturers of Shenmai injection was used to test the performance of the proposed method. The results showed that the classification accuracy reached 94.2%, obviously better than that of classical BP neural network (84.6%). It was verified that the new method could be used for fast evaluating the quality of chinese traditional medicine products.

Key words: quality evaluation of medicine, analysis of chinese traditional medicine, near infrared spectroscopy (NIRS), fuzzy neural network, fuzzy pattern classification