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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

Bamidele Victor Ayodele, Siti Indati Mustapa, Ramesh Kanthasamy, Norsyahida Mohammad, Abdulaziz Alturki, Thanikanti Sudhakar Babu

2022International Journal of Hydrogen Energy30 citationsDOI

Topics & Concepts

SyngasBiomass (ecology)Palm oilProcess engineeringCatalysisComputer scienceProcess (computing)AlgorithmHydrogenSupport vector machineHydrogen productionSequential quadratic programmingPulp and paper industryEnvironmental scienceQuadratic programmingChemistryMathematical optimizationMathematicsEngineeringOrganic chemistryMachine learningOceanographyAgroforestryGeologyOperating systemThermochemical Biomass Conversion ProcessesBiodiesel Production and ApplicationsEnergy and Environment Impacts
Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm | Litcius