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State-of-the-art least square support vector machine application for accurate determination of natural gas viscosity
, Article Industrial and Engineering Chemistry Research ; Vol. 53, issue. 2 , 2014 , pp. 945-958 ; ISSN: 08885885 ; Arabloo, M ; Shokrollahi, A ; Zargari, M. H ; Ghazanfari, M. H ; Sharif University of Technology
Abstract
Estimation of the viscosity of naturally occurring petroleum gases is essential to provide more accurate analysis of gas reservoir engineering problems. In this study, a new soft computing approach, namely, least square support vector machine (LSSVM) modeling, optimized with a coupled simulated annealing technique was applied for estimation of the natural gas viscosities at different temperature and pressure conditions. This model was developed based on 2485 viscosity data sets of 22 gas mixtures. The model predictions showed an average absolute relative error of 0.26% and a correlation coefficient of 0.99. The results of the proposed model were also compared with the well-known predictive...