The Effect of Nanomaterial Type on Water Disinfection Using Data Mining
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Applied Science Private University
Jadara University
Al-Zaytoonah University of Jordan
Technische Hochschule Ostwestfallen-Lippe
Corresponding author
Mohammad Ahmad Hamdan   

Applied Science Private University
J. Ecol. Eng. 2023; 24(4):244-251
Multiple linear regression and Artificial Neural Network (ANN) models were utilized in this study to assess the type influence of nanomaterials on polluted water disinfection. This was accomplished by estimating E. coli and the total coliform concentrations in contaminated water while nanoparticles were added at various concentrations as input variables, together with water temperature, PH, and turbidity. To achieve this objective, two approaches were implemented: data mining with two types of artificial neural networks (MLP and RBF), and multiple linear regression models (MLR). The simulation was conducted using SPSS software. Data mining was revealed after the estimated findings were checked against the measured data. It was found that MLP was the most promising model in the prediction of the TC and E.C concentration, s followed by the RBF and MLR models respectively.
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