ORIGINAL RESEARCH
Effect of Parametric Uncertainty of Selected
Classification Models and Simulations
of Wastewater Quality Indicators on Predicting
the Sludge Volume Index
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1
University of Agriculture in Cracow, Department of Sanitary Engineering and Water Management, Kraków, Poland
2
University of Agriculture in Cracow, Department of Ecology Climatology and Air Protection, Kraków, Poland
3
Slovak University of Agriculture in Nitra, Department of Water Resources and Environmental Engineering,
Nitra, Slovakia
Submission date: 2018-05-21
Final revision date: 2018-11-06
Acceptance date: 2018-11-21
Online publication date: 2019-10-30
Publication date: 2020-01-16
Corresponding author
Krzysztof Chmielowski
University of Agriculture in Cracow, Department of Sanitary Engineering and Water Management, al. Mickiewicza 24/28, 30-059 Kraków, Poland, al. Mickiewicza 24/28, 30-059 Kraków Kraków, Poland
Pol. J. Environ. Stud. 2020;29(2):1101-1110
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ABSTRACT
This article presents a method for assessing the impact of the predictive uncertainty of selected
wastewater quality indicators and the parametric uncertainty of classification models on the forecast
results of simulating activated sludge sedimentation using classification models. The data for the
calculations were obtained from monitoring carried out at a municipal wastewater treatment plant with
a capacity of 72,000 m3/d1, located in the Sitkówka-Nowiny commune. The treatment plant receives
wastewater, mostly from Kielce city. In the article the possibility of modeling the sedimentation of
activated sludge at a wastewater treatment plant using logistic regression and Gompertz models was
presented. The included values of the variables (i.e., sewage quality indicators) have been predicted
by black-box methods (support vectors and k-nearest neighbor). This approach can be used to improve
the operational efficiency of the bioreactor when continuous measurements of sewage quality are not
available.