Application of Artificial Neural Networks to Forecasting Total Nitrogen Content in Secondary Effluent from Treatment Plants

作者：Wasik Ewa^*; Chmielowski Krzysztof; Studzinski Jan; Szelag Bartosz

来源：Ochrona Srodowiska, 2018, 40(1): 29-33.

• Sewage
• secondary effluent
• modeling
• forecasting
• artificial neural networks
• total nitrogen
• ammonia nitrogen
• nitrites
• nitrates
• organic nitrogen

Potential application of artificial neural networks (ANN) to forecast total nitrogen content (TNC) in treated wastewater was presented as a function of selected nitrogen forms present in the secondary effluent. The analyzed data from the period of 2010-2016 covered measurements of the nitrogen content in the effluent from the treatment plant servicing agglomeration with a population equivalent of more than 100,000. The input data set was initially subjected to cluster analysis and then, used to train a neural network in the form of a multilayer perceptron (MLP). The simulations demonstrated that the smallest error values for the forecast of TNC (2-3%) were obtained for the variant, the value of which was a function of all the forms of nitrogen present in the secondary effluent. For the total nitrogen model based on inorganic nitrogen and nitrates data only, the simulation results did not differ significantly from the actual values, as indicated by a very high correlation coefficient (over 97%). In this case, the value of the mean absolute error increased only by nearly 4% to 6.2% (learning process) or 6.9% (testing/validation process), compared to the simulation based on all the nitrogen forms in the sewage.

• 出版日期2018