THE USE OF ARTIFICIAL NEURAL NETWORK TO PREDICT THE OPTIMAL COAGULANT DOSAGE OF MORINGA OLEIFRA SEED EXTRACT FOR WASTEWATER TREATMENT

ABSTRACT

This article presents the application of an Artificial Neural Network (ANN) layered architecture for optimal prediction. Coagulant dosage of Moringa oleifera seeds for drinking water treatment. The model was trained using a multi-layer perceptron (MLP) and evaluated on a new sample of data points. When evaluating the validity of the model, various evaluation indicators such as R2, standard error, and mean absolute error were used. Analysis showed Moringa oliefra seeds to be effective in reducing color and turbidity, with maximum turbidity removal being used at 0.02g per 100ml water sample.

This technique can be very much useful in the case of automating the process to check the optimal coagulant dosage.