Application of artificial neural networks to estimate wastewater treatment plant inlet biochemical oxygen demand

2008 ◽  
Vol 27 (4) ◽  
pp. 439-446 ◽  
Author(s):  
Emrah Dogan ◽  
Asude Ates ◽  
Ece Ceren Yilmaz ◽  
Beytullah Eren
Keyword(s):  
Neural Networks ◽  
Wastewater Treatment ◽  
Artificial Neural Networks ◽  
Biochemical Oxygen Demand ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Oxygen Demand ◽  
Artificial Neural

Integrated Wastewater Treatment Plant Performance Evaluation Using Artificial Neural Networks

1999 ◽  
Vol 40 (7) ◽  
pp. 55-65 ◽  
Author(s):  
Mohamed F. Hamoda ◽  
Ibrahim A. Al-Ghusain ◽  
Ahmed H. Hassan
Keyword(s):  
Neural Networks ◽  
Wastewater Treatment ◽  
Artificial Neural Networks ◽  
Wastewater Treatment Plant ◽  
Municipal Wastewater ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Plant Performance ◽  
Municipal Wastewater Treatment ◽  
Artificial Neural

Proper operation of municipal wastewater treatment plants is important in producing an effluent which meets quality requirements of regulatory agencies and in minimizing detrimental effects on the environment. This paper examined plant dynamics and modeling techniques with emphasis placed on the digital computing technology of Artificial Neural Networks (ANN). A backpropagation model was developed to model the municipal wastewater treatment plant at Ardiya, Kuwait City, Kuwait. Results obtained prove that Neural Networks present a versatile tool in modeling full-scale operational wastewater treatment plants and provide an alternative methodology for predicting the performance of treatment plants. The overall suspended solids (TSS) and organic pollutants (BOD) removal efficiencies achieved at Ardiya plant over a period of 16 months were 94.6 and 97.3 percent, respectively. Plant performance was adequately predicted using the backpropagation ANN model. The correlation coefficients between the predicted and actual effluent data using the best model was 0.72 for TSS compared to 0.74 for BOD. The best ANN structure does not necessarily mean the most number of hidden layers.

A sensitive ferricyanide-mediated biochemical oxygen demand assay for analysis of wastewater treatment plant influents and treated effluents

2013 ◽  
Vol 47 (2) ◽  
pp. 841-849 ◽  
Author(s):  
Mark A. Jordan ◽  
David T. Welsh ◽  
Richard John ◽  
Kylie Catterall ◽  
Peter R. Teasdale
Keyword(s):  
Wastewater Treatment ◽  
Biochemical Oxygen Demand ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Oxygen Demand ◽  
Treated Effluents

Biochemical oxygen demand prediction in wastewater treatment plant by using different regression analysis models

2019 ◽  
Vol 157 ◽  
pp. 79-89 ◽  
Author(s):  
Osman Tugrul Baki ◽  
◽  
Egemen Aras ◽  
Ummukulsum Ozel Akdemir ◽  
Banu Yilmaz
Keyword(s):  
Wastewater Treatment ◽  
Regression Analysis ◽  
Biochemical Oxygen Demand ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Oxygen Demand ◽  
Demand Prediction ◽  
Analysis Models
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