Study on proportion of pinellisa decoction for purging stomach-fire, ginger rind and licorice root with BP artificial neural network / 中国临床药理学与治疗学

ABSTRACT

AIM: To observe the difference in the application of proportion of pinellisa decoction for purging stomach-fire, ginger rind and licorice root with different BP (back propagation,BP) method of artificial neural network. METHODS: The influence of gastric mucuqas content in normal rats was measured, and the groups of different flavor of a drug and dosage were divided according to homogeneous design. This research was programmed with MATLAB6.5, conformed the experimental data with BP artificial neural network, and the research compared the different structural topology of 8-3-1?8-8-1?8-12-1, and compared the different influence with the different BP method to network. And then, the expected mode of gastric mucus content was formed, which based on the BP neural network. RESULTS: The artificial neural network model that had 8-10-1 structural topology and improved BP method was formed, and it was a kind of good method to uniform the studied samples and to forecast the unstudied samples, Moreover, the expected effect of variable learning rate back propagation was best. CONCLUSION: Using the studying of pinellisa decoction for purging stomach-fire, ginger rind and licorice as an example, and give birth to the new model in studying proportioning of compound prescription. This model will found its position in studying proportioning of compound prescription.