Abstract
Amoxicillin is a pharmaceutical pollutant that has severe impacts on aquatic life. Traditional treatment methods of Amoxicillin contaminated wastewater are expensive and inefficient. This paper uses soft computing to identify the best operating parameters of the solar photocatalysis process. The target is to maximize the degradation of Amoxicillin from wastewater. The proposed methodology integrates ANFIS modelling and grey wolf optimization (GWO). Three operating parameters are considered: TiO2 (g/L) dosage, initial antibiotic concentration (mg/L), and initial pH to maximize the AMX degradation (%). Based on experimental datasets, ANFIS model is designed to simulate the output solar photocatalysis process in terms of the mentioned operating parameters. The constructed ANFIS model is accurate; the R-squared values are 0.9982 and 0.9979 for training and testing. Then, using GWO, the best values of TiO2 (g/L), Amoxicillin (mg/L), and pH are determined. The results were compared with an optimized performance by response surface methodology and experimental data to demonstrate the superiority of the suggested methodology. The suggested methodology maximized the Amoxicillin (AMX) degradation by 3% while using higher initial AMX concertation by 60% and 90%, compared with the experimental and RSM methodologies. The results demonstrated the superiority of the proposed method in determining the adequate operating conditions while keeping the same operating conditions of the applied pH and TiO2 concentration.