@article{(Open Science Index):https://publications.waset.org/pdf/3844,
	  title     = {Prediction of Kinematic Viscosity of Binary Mixture of Poly (Ethylene Glycol) in Water using Artificial Neural Networks},
	  author    = {M. Mohagheghian and  A. M. Ghaedi and  A. Vafaei},
	  country	= {},
	  institution	= {},
	  abstract     = {An artificial neural network (ANN) model is
presented for the prediction of kinematic viscosity of binary mixtures
of poly (ethylene glycol) (PEG) in water as a function of temperature,
number-average molecular weight and mass fraction. Kinematic
viscosities data of aqueous solutions for PEG (0.55419×10-6 –
9.875×10-6 m2/s) were obtained from the literature for a wide range
of temperatures (277.15 - 338.15 K), number-average molecular
weight (200 -10000), and mass fraction (0.0 – 1.0). A three layer
feed-forward artificial neural network was employed. This model
predicts the kinematic viscosity with a mean square error (MSE) of
0.281 and the coefficient of determination (R2) of 0.983. The results
show that the kinematic viscosity of binary mixture of PEG in water
could be successfully predicted using an artificial neural network
model.},
	    journal   = {International Journal of Chemical and Molecular Engineering},
	  volume    = {5},
	  number    = {1},
	  year      = {2011},
	  pages     = {17 - 20},
	  ee        = {https://publications.waset.org/pdf/3844},
	  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},
	}