Research Article
Parametric and Nonparametric Approaches of Reid Vapor Pressure Prediction for Gasoline Containing Oxygenates: A Comparative Analysis Using Partial Least Squares, Nonlinear, and LOWESS Regression Modelling Strategies with Physical Properties
Table 3
Accuracy of PLSR, NLR, and NPR models for predicting gasoline RVP and comparison with previous studies.
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aPC-SAFT is perturbed-chain statistical associating fluid theory, and PSRK is predictive Soave-Redlich-Kwong equation adopted from Vella and Marshall [56], and they used data of gasoline and methanol blend taken from the experimental work of Andersen et al. [57]; bLI is Lagrange interpolating polynomial statistical method, and LS is least squares statistical fitting method adopted from Pumphrey et al. [58] for gasoline and isopropanol blend samples; cUNIFAC is universal quasichemical functional group activity coefficients adopted from Hatzioannidis et al. [59] for gasoline containing MTBE, methanol, ethanol, and isopropanol blends; dLSSVM is least squares support vector machine adopted from Kamari et al. [14] (considered for gasoline only); eANN is artificial neural network adopted from Albahri et al. [60] and considered for gasoline only; fSAFT-γ EoS is statistical associating fluid theory–Mie model equation of state adopted from Landera et al. [61]; gCPA is cubic plus association model adopted from Gaspar et al. [7]. |