Forecast the biological activity of nitrobenzene compound based on RBF neural network

At present, the multivariate linear regression analysis was adopted mostly in the biological toxicity forecast through establishment equation of the QSAR, but the error forecasted was big in many situations because of the complexity and nonlinearity of structure-activity relationship, and it has a high request to the sample selection, In this paper forecast model of the nitrobenzene compound biological toxicity has been established based on the RBF neural network. The studies suggest that the RBF network has the strong misalignment to approach ability, the fitting precision is good between the output and the sample, the result is better using the RBF network to forecast, the correlation coefficient has achieved 1.000, the prediction error in the permission scope, the biggest absolute value of error is 0.05 in this paper. So it is a good forecast mode of the nitrobenzene compound biological activity.