Application of multilayer perceptron network and random forest models for modelling the adsorption of chlorobenzene on a modifed bentonite by intercalation with hexadecyltrimethyl ammonium (HDTMA)
| dc.contributor.author | Nabil Bougdah | |
| dc.contributor.author | Salim Bousba | |
| dc.contributor.author | Youghourta Belhocine | |
| dc.contributor.author | Nabil Messikh | |
| dc.date.accessioned | 2024-05-22T09:14:24Z | |
| dc.date.available | 2024-05-22T09:14:24Z | |
| dc.date.issued | 2021-11-19 | |
| dc.description.abstract | Prediction of adsorption capacity, one of the most important properties of any adsorbent-adsorbate system, is crucial for adsorption studies. In this investigation, two approaches such as multilayer perceptron (MLP) and random forest (RF) were used to predict the adsorption capacity of hexadecyltrimethyl ammonium modifed bentonite to remove chlorobenzene (CB) from aqueous solution. The adsorption study was conducted in batch mode at diferent adsorption parameters. The results show that the adsorption processes were best described by Freundlich isotherm model, while the adsorption mechanism followed the pseudo-second order kinetics. It was observed that the structure of MLP model that give the best prediction consisted of three layers: input layer with four neurons, output layer with one neuron, and four neurons at hidden layer. The three important parameters for RF model were ntree=500, mtry=1, and node size=1. According to the results obtained, the MLP model provided slightly higher levels of accuracy with a consistently high coefcient of determination (R2=0.996) and low root mean square error (RMSE=0.00101) compared to RF model. (R2=0.969, RMSE=0.03008). Therefore, the initial concentration of CB with 35.29%, appeared to be the most infuential parameter in the adsorption of CB on the modifed bentonite. | |
| dc.identifier.uri | http://dspace.univ-skikda.dz:4000/handle/123456789/1820 | |
| dc.language.iso | en | |
| dc.publisher | Reaction Kinetics, Mechanisms and Catalysis | |
| dc.title | Application of multilayer perceptron network and random forest models for modelling the adsorption of chlorobenzene on a modifed bentonite by intercalation with hexadecyltrimethyl ammonium (HDTMA) | |
| dc.type | Article |