Neural network analysis in the study of the QSAR of ternary dissymmetric organic phosphate insecticide

By use of the improved neural network method Generalized error Back Propagation (GBP) combined with the multiple linear regression(MLR),a quantitative structure activity relationship(QSAR) of a set of 22 O ethyl N alkyl(substituted thioureido) phosphoamidethioates insecticides was studied. The significant parameters were determined by R type cluster.Although the regression method gave physical explanations,it couldn′t analize the non linear QSAR.The non linear relationships between the structure and the activity were studied by GBP method with 4-4-1 network.The study rate was 0.5,modified factor was 0.05.The cross validation was used by leave one out method to avoid the overfitting phenomena.The relative errors of the prediction was 0.027.The result of study show that the neural network can play an important role in non linear QSAR and give out a more accurate model for QSAR.