Identification and Prediction of Wastewater Treatment Parameters
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In this paper, neural networks are extensively used to identify and predict wastewater process parameters. Three methods are implemented to control the system operations. The difference neural network inputs are excluded in the first method and considered in the second one. The third one is implemented using the extended Kalman filter. High performance is obtained by our approach, which considers input difference effects and, therefore, fits better to overcome the complex wastewater problem.
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