LU Chao, YANG Cuili, QIAO Junfei. Soft-computing Method for Ammonia Nitrogen Prediction Based on Spiking Self-organizing RBF Neural Network[J]. INFORMATION AND CONTROL, 2017, 46(6): 752-758. DOI: 10.13976/j.cnki.xk.2017.0752
Citation: LU Chao, YANG Cuili, QIAO Junfei. Soft-computing Method for Ammonia Nitrogen Prediction Based on Spiking Self-organizing RBF Neural Network[J]. INFORMATION AND CONTROL, 2017, 46(6): 752-758. DOI: 10.13976/j.cnki.xk.2017.0752

Soft-computing Method for Ammonia Nitrogen Prediction Based on Spiking Self-organizing RBF Neural Network

  • In order to solve the problem of ammonia nitrogen online detection in wastewater treatment process, we propose a soft-computing method based on spiking self-organizing RBF neural network. Firstly, we select the auxiliary variables which have a great influence on the prediction of ammonia nitrogen. Secondly, we use the SSORBF neural network to establish the nonlinear relationship between main variables and predicted variables. Secondly, we take the spike mechanism and gradient descent algorithm to adjust the network structure and parameters. Finally, we apply the method to measuring the effluent NH4-N concentration in a real wastewater treatment process. Simulation results show that this method can effectively realize the online prediction of ammonia nitrogen concentration, improve the prediction accuracy and adaptive ability.
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