Title :
Forecast the Biological Activity of Nitrobenzene Compound Based on BP Neural Network
Author :
HuiYu Jiang ; HuiYong Jiang ; Wei, Tao ; Yang, Feng
Author_Institution :
Dept. of Chem. Eng., Wuhan Univ. of Sci. & Eng., Wuhan
Abstract :
At present, the multivariate linear regression analysis was adopted in the biological toxicity forecast through establishment equation of the QSAR mostly, 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 Levenberg_Marquardt BP neural network in this paper, The studies suggest that the BP 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 BP network to forecast, the correlation coefficient has achieved 0.999, 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.
Keywords :
backpropagation; biology computing; chemical hazards; neural nets; nitrogen compounds; regression analysis; toxicology; Levenberg_Marquardt BP neural network; QSAR; biological activity; biological toxicity forecast; multivariate linear regression analysis; nitrobenzene compound; sample selectionjn; structure-activity relationship; Artificial neural networks; Biology; Chemical industry; Convergence; Feedforward systems; Linear regression; Neural networks; Neurons; Nonlinear equations; Signal processing;
Conference_Titel :
Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3490-9
DOI :
10.1109/PACIIA.2008.209