Online prediction model based on fuzzy neural network for the effluent ammonia concentration of A~2/O system

Based on the prototype experiment of treating synthetic wastewater in anaerobic/anoxic/oxic(A2/O) wastewater treatment system,an artificial neural network(ANN) model and an adaptive network based fuzzy inference system(ANFIS) model were employed to simulate the treatment process.When constructing the online prediction model in MATLAB,the online monitoring parameters,namely hydraulic retention time(HRT),influent pH(pH),dissolved oxygen(DO),and mixed-liquid return ratio(r),were adopted as the input variables,and effluent ammonia concentration(NH4+eff) was used as output variable.A self-adapted fuzzy c-means clustering algorithm was used to identify the fuzzy rules and optimize the model's operational parameters.The simulation results shown that,compared with the ANN model,the ANFIS model's predicted effluent ammonia concentrations fitted the observed ones better,which was supported by the maximum relative error of 6.45%,mean absolute percentage error(MAPE) of 2.8%,root mean square error(RMSE) of 0.1209,and correlation coefficient(R) value of 0.9956.Furthermore,3D surfaces obtained during the model training,which directly reflected the non-linear function between the factors and the effluent ammonia concentration,can guide the efficient and stable operation of the A2/O system.