摘要
采用Chemoffice8.0中的MOPAC-AM1算法对多氯代二苯并-对-二恶英(PCDDs)化合物的量子化学结构参数进行计算,并将筛选后的量化参数作为PCDDs分子的结构描述符,利用人工神经网络中的反向传播网络和径向基函数网络建立分子结构与正辛醇/水分配系数间的相关模型并进行预测,并将所得结果与多元回归方法的结果进行对比分析发现:反向传播网络和径向基函数网络所得结果均优于多元回归方法.
The structure parameters of the quantum chemistry for polychlorinated dibenzo-p-dioxins（PCDDs） compounds are calculated by using the MOPAC-AM1 method in Chemoffice8.0.Some parameters are selected as the structure descriptors of PCDDs compound.The molecular structure and the model of n-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.
出处
《河北师范大学学报（自然科学版）》
CAS
北大核心
2010年第1期73-77,80,共6页
Journal of Hebei Normal University：Natural Science
基金
国家自然科学基金(30760195)
