Modeling of energy consumption and effluent quality using density peaks-based adaptive fuzzy neural network

Modeling of energy consumption ( EC ) and effluent quality ( EQ ) are very essential problems that need to be solved for the multiobjective optimal control in the wastewater treatment process ( WWTP ). To address this issue, a density peaks-based adaptive fuzzy neural network ( DP-AFNN ) is proposed in this study. To obtain suitable fuzzy rules, a DP-based clustering method is applied to fit the cluster centers to process nonlinearity. The parameters of the extracted fuzzy rules are fine-tuned based on the improved Levenberg-Marquardt algorithm during the training process. Furthermore, the analysis of convergence is performed to guarantee the successful application of the DPAFNN. Finally, the proposed DP-AFNN is utilized to develop the models of EC and EQ in the WWTP. The experimental results show that the proposed DP-AFNN can achieve fast convergence speed and high prediction accuracy in comparison with some existing methods.