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Year: 2008 | Volume: 3 | Issue: 1 | Page No.: 38 - 46
S. Boulahbel, L. Saad Saoud and A. Khellaf
Abstract
In this study, neural networks are extensively used to identify and predict wastewater process parameters. Three methods are implemented to drive the system’s operation. In the first one difference neural networks inputs are ignored but considered in the second, an extended Kalman filter implements the third one. High performance is derived from our approach which considers input difference effects and therefore, fits better to overcome the complex wastewater problem.