Wastewater Treatment System Modeling Based on High-Order Recurrent Neural Network

Aiming at the characteristics of wastewater treatment process such as multi-variable,nonlinearity,large time delay and strong coupling,a modeling method using recurrent high-order neural network（RHONN） is proposed to establish models for the key parameters,including chemical oxygen demand,biological oxygen demand,suspended solid and NH₄-N. This modeling method is then applied to a certain wastewater treatment plant's actual running data during biological reaction process.The simulation results demonstrate that the proposed method is effective.The comparisons with the feed-forward neural network and first-order recurrent neural network show mat the modeling results by the recurrent high-order neural network own higher accuracy.