首页|Investigators from University of Ferhat Abbas Have Reported New Data on Support Vector Machines (Thermodynamic Study and the Development of a Support Vector Mac hine Model for Predicting Adsorption Behavior of Orange Peel-derived Beads In .. .)
Investigators from University of Ferhat Abbas Have Reported New Data on Support Vector Machines (Thermodynamic Study and the Development of a Support Vector Mac hine Model for Predicting Adsorption Behavior of Orange Peel-derived Beads In .. .)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Su pport Vector Machines. According to news reporting originating from Setif, Alger ia, by NewsRx correspondents, research stated, “This study investigates the use of orange peels as a precursor for synthesizing sodium alginate -encapsulated be ads for methylene blue (MB) removal. The prepared beads (BOP1 and BOP2) underwen t characterization through FTIR, XRF, SEM and TGA.” Financial supporters for this research include MESRS, DGRSDT. Our news editors obtained a quote from the research from the University of Ferha t Abbas, “Subsequently, the impacts of various factors, including temperature, t he initial pH, initial concentration, salt and humic acid, are studied. The adso rption isotherms show high adsorbed quantities of 764.92 and 659.78 mg/g for BOP 1 and BOP2 respectively, while the obtained data are best described by the monol ayer with two energies (MMTE) model, which is then used to perform a thermodynam ic study of the MB adsorption mechanism. Additionally, the adsorption kinetics d ata are modeled using three models, with the PFO model identified as the most ap propriate. The regenerated beads demonstrate the ability to be reused up to 7 cy cles, The effects of NaCl and humic acid on MB adsorption reveal that NaCl inhib its adsorption due to competition with Na +, while humic acid has no effect. Fin ally, a support vector machine (SVM) model optimized by the Levy Flight Distribu tion Optimization (LFD) algorithm is developed and found to be capable of accura tely predicting the adsorption behavior of the prepared beads. This model is the n used in optimizing the process conditions for maximal MB removal.”
SetifAlgeriaEmerging TechnologiesM achine LearningSupport Vector MachinesVector MachinesUniversity of Ferhat Abbas
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