安徽农业科学2012，Vol.40Issue(4)：2087-2089,3.
人工神经网络用于有机磷酸酯类定量结构活性关系研究
QSAR Study of Organophosphate Compounds Using Artificial Neural Network
摘要
Abstract
The systematic study of the quantitative structure-activity relationship ( QSAR) on 35 organophosphate compounds was performed based on the artificial neural network. For the artificial neural network method, when using the molecular electronegativity-distance vector as the inputs of the neural network and the acute toxicity to housefly as the outputs of the neural network, the correlation coefficient of established model was 0.999 9, the leave one out cross-validation regression coefficient was 0.995 8, the standard error was 0.114 1, the correlation coefficient of the test set was 0.986 0 and the absolute values of residual were less than or equal to 0.40. In order to make contrast, the QSAR model was set up by multiple linear regressions (MLR) method. For the model built by MLR, the correlation coefficient was 0. 976 0, the standard error was 0. 256 8 and the absolute values of residual were less than or equal to 0.57, the correlation coefficient of the test set was 0. 975 8. The results showed that the performance of neural network method is better than that of MLR method.关键词
有机磷酸酯类化合物/定量结构活性关系/人工神经网络/急性毒性Key words
Organophosphate compounds/ Quantitative structure-activity relationship/ Artificial neural network/ Acute toxicity分类
化学化工引用本文复制引用
何琴,黄保军..人工神经网络用于有机磷酸酯类定量结构活性关系研究[J].安徽农业科学,2012,40(4):2087-2089,3.基金项目
河南省教育厅自然科学研究计划项目(2009B150023) （2009B150023）
