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The purpose of the present research was to estimate the heat of vaporization for petroleum fractions and pure hydrocarbons by the least-square support vector machine (LSSVM) as a function of the specific gravity, molecular weight, and boiling point temperature. Moreover, a particle swarm optimization technique was applied to determine optimal dependent parameters of LSSVM. In addition, results obtained from the proposed LSSVM model have been compared to some developed correlations by scholars. According to statistical observations, the LSSVM model has acceptable predictions by the value of mean relative deviation and R-squared (R2) equal to 0.51% and 0.9998, respectively. The present predictive manner can be used in petroleum engineering for an accurate approximation of heat of vaporization.
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Ahmadi et al. (2019) studied this question.
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