Method for effluent total nitrogen-based on a recurrent self-organizing RBF neural network
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United States of America
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Feb 25, 2020
Grant Date -
Feb 1, 2018
app pub date -
Dec 23, 2016
filing date -
Dec 23, 2016
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Abstract
In this present disclosure, a computing implemented method is designed for predicting the effluent total nitrogen concentration (TN) in an urban wastewater treatment process (WWTP). The technology of this present disclosure is part of advanced manufacturing technology and belongs to both the field of control engineer and environment engineer. To improve the predicting efficiency, a recurrent self-organizing radial basis function (RBF) neural network (RSORBFNN) can adjust the structure and parameters simultaneously. This RSORBFNN is developed to implement this method, and then the proposed RSORBFNN-based method can predict the effluent TN concentration with acceptable accuracy. Moreover, online information of effluent TN concentration may be predicted by this computing implemented method to enhance the quality monitoring level to alleviate the current situation of wastewater and to strengthen the management of WWTP.
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