Prediction of research octane number loss and sulfur content in gasoline refining using machine learning
Fengyu Zhang, Xinchao Su, Aoli Tan, Jingjing Yao, Haipu Li
Topics & Concepts
Mean squared errorLinear regressionArtificial neural networkGasolineCorrelation coefficientComputer scienceMean absolute percentage errorRandom forestGradient boostingBoosting (machine learning)GeneralizationDecision treeRefining (metallurgy)Octane ratingArtificial intelligenceMachine learningMathematicsStatisticsChemistryPhysical chemistryMathematical analysisOrganic chemistryCatalysis and Hydrodesulfurization StudiesPetroleum Processing and AnalysisProcess Optimization and Integration