广西师范大学学报（自然科学版）2011，Vol.29Issue(4)：92-98,7.
人工神经网络预测多氯代二苯并呋喃类化合物的正辛醇/水分配系数
Predicting n-Octanol/Water Partition Coefficients of Polychlorinated Dibenzofurans with Artificial Neural Network
摘要
Abstract
The structure parameters of the quantum chemistry for polychlorinated dibenzofurans (PCD-Fs) compounds were calculated by using the MOP AC-AMI method in Chemoffice 8. 0. Some parameters are selected as the structure descriptors of PCDFs compounds. The molecular structures and the model of w-octanol/water partition coefficients are constructed and predicted in terms of back-propagation network and radial basis function networks in artificial neural network. These results are compared with the results of multiple regression methods. It can be found that the results of back-propagation network and radial basis function networks are better than those of multiple regression methods.关键词
人工神经网络/多氯代二苯并呋喃/正辛醇/水分配系数Key words
artificial neural network/polychlorinated dibenzofurans/n-octanol/water partition coefficients分类
化学化工引用本文复制引用
俞青芬..人工神经网络预测多氯代二苯并呋喃类化合物的正辛醇/水分配系数[J].广西师范大学学报（自然科学版）,2011,29(4):92-98,7.基金项目
国家自然科学基金资助项目(30760195) （30760195）
