Artificial neural network (ANN) approach for modeling of selected biogenic compounds in a mixture of treated municipal and dairy wastewater

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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Main Authors: Struk-Sokołowska Joanna, Ofman Piotr, Demirel Sevgi
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/26/e3sconf_eko-dok2019_00077.pdf
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spelling 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
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AT ofmanpiotr artificialneuralnetworkannapproachformodelingofselectedbiogeniccompoundsinamixtureoftreatedmunicipalanddairywastewater
AT demirelsevgi artificialneuralnetworkannapproachformodelingofselectedbiogeniccompoundsinamixtureoftreatedmunicipalanddairywastewater
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