%0 Journal Article
	%A E. Nemati Lay and  M. Peymani and  E. Sanjari
	%D 2012
	%J International Journal of Chemical and Molecular Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 67, 2012
	%T Prediction of Natural Gas Viscosity using Artificial Neural Network Approach
	%U https://publications.waset.org/pdf/7460
	%V 67
	%X Prediction of viscosity of natural gas is an important parameter in the energy industries such as natural gas storage and transportation. In this study viscosity of different compositions of natural gas is modeled by using an artificial neural network (ANN) based on back-propagation method. A reliable database including more than 3841 experimental data of viscosity for testing and training of ANN is used. The designed neural network can predict the natural gas viscosity using pseudo-reduced pressure and pseudo-reduced temperature with AARD% of 0.221. The accuracy of designed ANN has been compared to other published empirical models. The comparison indicates that the proposed method can provide accurate results.

	%P 577 - 583