Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks
A sequencing batch reactor was modeled using multi-layer perceptron and radial basis
function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent
concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and
MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and
NH 4+-N. The results showed that the optimal removal efficiencies would be obtained at FT
of 1 h, RT of 6 h, aeration intensity of 0.88 m 3/min and SRT of 30 days. In addition, COD and …
function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent
concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and
MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and
NH 4+-N. The results showed that the optimal removal efficiencies would be obtained at FT
of 1 h, RT of 6 h, aeration intensity of 0.88 m 3/min and SRT of 30 days. In addition, COD and …
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