Dragonfly Support Vector Machine Modelling of the Adsorption Phenomenon of Certain Phenols by Activated Carbon Fibres

Abstract

The objective of this research was to build a mathematical model based on a Support Vector Machine (SVM) capable of predicting the amount adsorbed at equilibrium (qe). Activated carbon fibres (ACF) were used for the adsorption of certain phenols (phenol, 2-chlorophenol, 4-chlorophenol, 2,4,6-trichlorophenol, 4-nitrophenol, and 2,4-dinitrophenol). An experimental dataset of 129 points was collected from previously published papers. The inputs considered for modelling were temperature (T), concentration at equilibrium (ce), and two descriptors (boiling point (BP) and density (d)) to differentiate between the pollutants studied. The data used were pre-processed by the statistical analysis to ensure that they were adequate for modelling. The results showed a superiority of the Gaussian kernel function DA-SVM model demonstrated by its determination coefficient (R2 = 0.997) and root mean squared error (RMSE = 0.027 mmol l−1).

Keywords

• adsorption
• phenols
• support vector machine
• dragonfly algorithm
• activated carbon fibre
• amount adsorbed at equilibrium