Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater
This paper presents artificial neural network (ANN) model of wastewater treatment plant, which was used for average monthly concentrations of N-NH4+, N-NO3-, N-NO2-, total Kiejdahl nitrogen (TKN), PO43- and SO42- approximation. ANN model was developed for wastewater treatment plant located in Bystre...
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2019-01-01
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doaj-80d102c65e3f401dacb394ef84204b1f2021-02-02T07:04:27ZengEDP SciencesE3S Web of Conferences2267-12422019-01-011000007710.1051/e3sconf/201910000077e3sconf_eko-dok2019_00077Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewaterStruk-Sokołowska Joanna0Ofman Piotr1Demirel Sevgi2Bialystok University of Technology, Department of Civil and Enviromental Engineering Technology and SystemsBialystok University of Technology, Department of Civil and Enviromental Engineering Technology and SystemsNiğde Ömer Halisdemir University, Department of Environmental EngineeringThis paper presents artificial neural network (ANN) model of wastewater treatment plant, which was used for average monthly concentrations of N-NH4+, N-NO3-, N-NO2-, total Kiejdahl nitrogen (TKN), PO43- and SO42- approximation. ANN model was developed for wastewater treatment plant located in Bystre, Poland which treats municipal wastewater with a share of dairy wastewater. The object was chosen because of the unique location, in the Great Mazury Lakes area and the need for its special environmental protection. Input layer of developed ANN model consisted of BOD, COD, concentrations of total nitrogen and total phosphorus, total organic carbon, sulphates, wastewater temperature and pH., The developed model reflected extreme values observed during study period. Average error percentage with which output variables were approximated equalled to 35.35%; 8.99%; 21.23%; 5.08%; 10.99%; 3.02% respectively for N-NH4+, N-NO3-, N-NO2-, TKN, PO43- and SO42-.https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/26/e3sconf_eko-dok2019_00077.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Struk-Sokołowska Joanna Ofman Piotr Demirel Sevgi |
spellingShingle |
Struk-Sokołowska Joanna Ofman Piotr Demirel Sevgi Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater E3S Web of Conferences |
author_facet |
Struk-Sokołowska Joanna Ofman Piotr Demirel Sevgi |
author_sort |
Struk-Sokołowska Joanna |
title |
Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater |
title_short |
Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater |
title_full |
Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater |
title_fullStr |
Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater |
title_full_unstemmed |
Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater |
title_sort |
artificial neural network (ann) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater |
publisher |
EDP Sciences |
series |
E3S Web of Conferences |
issn |
2267-1242 |
publishDate |
2019-01-01 |
description |
This paper presents artificial neural network (ANN) model of wastewater treatment plant, which was used for average monthly concentrations of N-NH4+, N-NO3-, N-NO2-, total Kiejdahl nitrogen (TKN), PO43- and SO42- approximation. ANN model was developed for wastewater treatment plant located in Bystre, Poland which treats municipal wastewater with a share of dairy wastewater. The object was chosen because of the unique location, in the Great Mazury Lakes area and the need for its special environmental protection. Input layer of developed ANN model consisted of BOD, COD, concentrations of total nitrogen and total phosphorus, total organic carbon, sulphates, wastewater temperature and pH., The developed model reflected extreme values observed during study period. Average error percentage with which output variables were approximated equalled to 35.35%; 8.99%; 21.23%; 5.08%; 10.99%; 3.02% respectively for N-NH4+, N-NO3-, N-NO2-, TKN, PO43- and SO42-. |
url |
https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/26/e3sconf_eko-dok2019_00077.pdf |
work_keys_str_mv |
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