【摘要】 目的 :应用BP人工神经网络 ,建立半夏泻心汤不同配伍与胃蛋白酶间的非线性映射模型。方法 :应用均匀设计表给出半夏泻心汤中药物及生姜共 8味药物不同配伍组合 ,共形成 2 4组 ,采用安宋氏法测定不同组别对正常大鼠胃蛋白酶活性的影响 ,应用MATLAB 6 .5进行编程 ,选用BP人工神经网络拟合实验数据 ,其中 2 1组作为学习样本 ,建立模型 ,另外 3组作为未学习样本 ,验证模型的预测能力。结果 :通过对 2 1组实验数据的学习 ,建立了拓扑结构为 8 10 1的BP网络模型 ,所建模型可以很好的拟合学习过的样本 ,并且可以很好地预测未学习过的样本 ,预测值和实际值之间的相关性系数r=0 .94 33。结论 :BP神经网络可以很好的拟合复方配伍中复杂的非线性关系 ,可以应用于复方配伍研究的建模。更多还原

【Abstract】 AIM : To set up the non linear corresponding experimental data model between the ingredients compatibility of proportioning of pinellisa decoction for purging stomach fire and gastric protease by BP artificial neural network. METHODS : 24 groups were formed based on 8 kinds of medical herbs including ginger rind and herbal ingredients in proportioning of pinellisa decoction for purging stomach fire according to homogeneous design. The influence of the activity of gastric protease in normal rats was measured by ansongshifa. The research was programmed by MATLAB 6.5, and the experimental data was conformed by BP artificial neural network. In the 24 groups, 21 groups as samples were studied to form the model, and the other 3 groups as the unstudied samples were test and verify the forecast ability of data. RESULTS : BP artificial neural network that had 8 10 1 structural topology was formed according to the study of the experiment data in 21 groups. It was a kind of good method to uniform the studied samples and to forecast the unstudied samples, and the interrelated coefficient in the forecast value and reality value was 0.9433 . CONCLUSION : The BP artificial neural network shows the excellent ability of self organization and self acclimation, and it conforms to the complicated non linear relation during the proportioning of compound prescriptions.更多还原