Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network - Afrand, M.; Nazari Najafabadi, K.; Sina, N.; Safaei, M.R.; Kherbeet, A.Sh.; Wongwises, S.; Dahari, M. (Elsevier, 2016)
In this paper, at first, a new correlation was proposed to predict the relative viscosity of MWCNTs-SiO2/AE40 nano-lubricant using experimental data. Then, considering minimum prediction error, an optimal artificial neural network was designed to predict the relative viscosity of the nano-lubricant. Forty-eight experimental data were used to feed the model. The data set was derived to training, validation and test sets which contained 70%, 15% and 15% of data points, respectively. The correlation outputs showed that there is a deviation margin of 4%. The results obtained from optimal artificial neural network presented a deviation margin of 1.5%. It can be found from comparisons that the optimal artificial neural network model is more accurate compared to empirical correlation.