Modeling the Solubility of Sulfur in Sour Gas Mixtures Using Improved Support Vector Machine Methods
Yu-Chen Wang, Zhengshan Luo, Yiqiong Gao, Yulei Kong
Abstract
) is as high as 0.9987, and the prediction accuracy is much higher than that of other models.
Topics & Concepts
SolubilitySupport vector machineLeast squares support vector machineSulfurSour gasComputer sciencePartial least squares regressionOutlierAlgorithmArtificial intelligenceChemistryMachine learningNatural gasOrganic chemistryIndustrial Gas Emission ControlAir Quality Monitoring and ForecastingMetaheuristic Optimization Algorithms Research