Predicting aluminium using full-scale data of a conventional water treatment plant on Orontes River by ANN, GEP, and DT
by Ruba Dahham Alsaeed; Bassam Alaji; Mazen Ibrahim
International Journal of Water (IJW), Vol. 15, No. 3, 2023

Abstract: Aluminium sulphate is one of the most common chemicals used to coagulate water. Some studies indicate that it can increase the risk of Alzheimer's disease. This study focused on the relationship between residual aluminium and many parameters. The actual data of Al-Qusayr purification plant in Homs city was used. Three different models were studied, artificial neural networks (ANN), genetic expression technology (GEP) and Decision Tree (DT), to determine the residual aluminium. The models' results were compared. ANN was the best in modelling data when initial turbidity was between 6.5 and 30 NTU, decision tree was better in the range 25 to 60 NTU. In general the best model was ANN, while the most easily generalised one was GEP. The ANN model was found to be the most suitable model to predict residual aluminium with a coefficient of determination R² = 0.88 and RMSE = 0.019 mg/L.

Online publication date: Mon, 09-Oct-2023

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