基于RBF网络的氨酚曲马多个体药代动力学参数预测模型  

Forecasting Model of Individual Pharmaceutical Parameter of Paracetamol and Tramadol Hydrochloride based on RBF Network

作　　者：黄榕波[1] 郭穗勋[1] 

机构地区：[1]广东药学院基础学院,广东广州510006

出　　处：《琼州学院学报》2013年第5期14-18,共5页Journal of Qiongzhou University

基　　金：国家自然科学基金资助项目(10926191)

摘　　要：建立基于径向基函数网络(Radial Basis Function network,RBF)的个体差异与药代动力学参数之间的关系模型.应用主成分分析(Principal Component Analysis,PCA)从个体差异因子中获取主成分作为RBF的输入,降低RBF的输入维数,从而降低了系统的复杂性.通过健康志愿者获得的实验数据对模型进行测试,实验结果表明RBF模型具有良好的拟合能力.The model between pharmaceutical parameters and individual difference was constructed based on RBF network. The principal components extracted from the individual difference by PCA technique were used as RBF input. The system complexity was reduced by reducing RBF input dimension with PCA. The results show that the RBF model has good fitting ability.

关 键 词：RBF 药代动力学 PCA 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] R969.1[自动化与计算机技术—控制科学与工程]