Modeling of a Wastewater Treatment Process Using Neural Networks

This research deals with the use of artificial neural networks for modeling a nonlinear biotechnological process, thus approximating a nonlinear function. In the absence of a mathematical model, an artificial neural network trained with a set of representative data can successfully replace and predict the system's behavior in time. Furthermore, this approximation is useful in the identification algorithms, prediction and diagnosis of different biotechnological systems. The biotechnological system considered in this research is a biological wastewater treatment process with active sludge.