Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4389558 | Ecological Engineering | 2014 | 9 Pages |
•An integrated SBBR-VFCW system was applied to the wastewater treatment.•An ANN simulation study was evaluated.•SBBR-VFCW system can purify the wastewater effectively.•ANN is suitable for the dynamic monitor for SBBR-VFCW wastewater treatment.
In this study, a sequencing batch biofilm reactor combined with a vertical flow constructed wetland (SBBR-VFCW) system was constructed and applied to the wastewater treatment. Thalia dealbatas were planted in the VFCW. The artificial neural network (ANN) was used to simulate and predict the performance of SBBR-VFCW. The results showed that when the concentrations of COD, NH4+-N, TN and TP in the wastewater were 200.22 mg/L, 48.11 mg/L, 48.11 mg/L and 6.11 mg/L respectively, the removal efficiencies were 97.0%, 98.5%, 91.5% and 88.5%, correspondingly, which indicated that the SBBR-VFCW system can treat the wastewater effectively. According to the results of the ANN simulation analysis, the correlation coefficients (R2) were all higher than 0.99, and the root mean squared errors (RMSE) were lower than 0.0782. The concentrations of DO, NH4+-N and TP in the influent exhibited strong impacts on the effluent. This study reveals that the ANN can efficiently reflect the nonlinear function of each factor, and is suitable for the dynamic monitoring of SBBR-VFCW treatment for wastewater in various conditions.
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