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In this paper, we propose a high order neural network (HONN) trained with an extended Kalman filter based algorithm to predict wind speed. Due to the chaotic behavior of the wind time series, it is not possible satisfactorily to apply the traditional forecasting techniques for time series; however, the results presented in this paper confirm that HONNs can very well capture the complexity underlying...
This paper presents a neural network identification scheme to estimate substrate, biomass and dissolved oxygen concentrations in an activated sludge wastewater treatment. This scheme is based on a discrete-time high order neural network (RHONN) trained on-line with an extended Kalman filter (EKF)-based algorithm. Then, the identification scheme is associated with a fuzzy control to regulate the ratio...
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