@article{(Open Science Index):https://publications.waset.org/pdf/604,
	  title     = {Correlation of Viscosity in Nanofluids using Genetic Algorithm-neural Network (GA-NN)},
	  author    = {Hajir Karimi and  Fakheri Yousefi and  Mahmood Reza Rahimi},
	  country	= {},
	  institution	= {},
	  abstract     = {An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.},
	    journal   = {International Journal of Chemical and Molecular Engineering},
	  volume    = {5},
	  number    = {1},
	  year      = {2011},
	  pages     = {53 - 60},
	  ee        = {https://publications.waset.org/pdf/604},
	  url   	= {https://publications.waset.org/vol/49},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 49, 2011},
	}