Modelling of coagulant dosage in a water treatment plant

The coagulation-flocculation is a major step in the drinkable water treatment process allowing the removal of colloidal particles. The water treatment facilities of the City of Sainte-Foy have been well instrumented and process variables such as temperature, pH, turbidity, conductivity of raw and treated water along with actual coagulant dosage available have been measured and stored each 5 min for several years. Using such a data bank, the objective of this paper is to report on the development of a neural network predictor of coagulant dosage in order to facilitate process operation. Feedforward neural models have been built using a quasi-Newton method along with the early stopping approach to avoid overfitting. Annual and seasonal models have been built and their performances are discussed. (C) 1997 Elsevier Science Limited.