Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)

Wastewater treatment plants (WWTPs) are highly complicated and dynamic systems and so their appropriate operation, control, and accurate simulation are essential. The simulation of WWTPs according to the process complexity has become an important issue in growing environmental awareness. In recent d...

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Autores principales:	Nasim Hejabi, Seyed Mahdi Saghebian, Mohammad Taghi Aalami, Vahid Nourani
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	effluent quality ensemble approach monte carlo method support vector machine uncertainty wastewater treatment plant Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/990119d14fb34a4a9df2d0f1b572f276
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spelling	oai:doaj.org-article:990119d14fb34a4a9df2d0f1b572f2762021-11-06T10:54:16ZEvaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)0273-12231996-973210.2166/wst.2021.067https://doaj.org/article/990119d14fb34a4a9df2d0f1b572f2762021-04-01T00:00:00Zhttp://wst.iwaponline.com/content/83/7/1633https://doaj.org/toc/0273-1223https://doaj.org/toc/1996-9732Wastewater treatment plants (WWTPs) are highly complicated and dynamic systems and so their appropriate operation, control, and accurate simulation are essential. The simulation of WWTPs according to the process complexity has become an important issue in growing environmental awareness. In recent decades, artificial intelligence approaches have been used as effective tools in order to investigate environmental engineering issues. In this study, the effluent quality of Tabriz WWTP was assessed using two intelligence models, namely support Vector Machine (SVM) and artificial neural network (ANN). In this regard, several models were developed based on influent variables and tested via SVM and ANN methods. Three time scales, daily, weekly, and monthly, were investigated in the modeling process. On the other hand, since applied methods were sensitive to input variables, the Monte Carlo uncertainty analysis method was used to investigate the best-applied model dependability. It was found that both models had an acceptable degree of uncertainty in modeling the effluent quality of Tabriz WWTP. Next, ensemble approaches were applied to improve the prediction performance of Tabriz WWTP. The obtained results comparison showed that the ensemble methods represented better efficiency than single approaches in predicting the performance of Tabriz WWTP. HIGHLIGHTS SVM and FFNN methods were applied as alternatives to mathematical models to describe the behavior of WWTPs and deal with the complexity of the WWTP.; Daily, weekly, and monthly time scales were investigated in the modeling process.; The Monte Carlo method was used to evaluate the uncertainty of applied models.; The impact of ensemble approaches on improving the prediction performance was assessed.;Nasim HejabiSeyed Mahdi SaghebianMohammad Taghi AalamiVahid NouraniIWA Publishingarticleeffluent qualityensemble approachmonte carlo methodsupport vector machineuncertaintywastewater treatment plantEnvironmental technology. Sanitary engineeringTD1-1066ENWater Science and Technology, Vol 83, Iss 7, Pp 1633-1648 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	effluent quality ensemble approach monte carlo method support vector machine uncertainty wastewater treatment plant Environmental technology. Sanitary engineering TD1-1066
spellingShingle	effluent quality ensemble approach monte carlo method support vector machine uncertainty wastewater treatment plant Environmental technology. Sanitary engineering TD1-1066 Nasim Hejabi Seyed Mahdi Saghebian Mohammad Taghi Aalami Vahid Nourani Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
description	Wastewater treatment plants (WWTPs) are highly complicated and dynamic systems and so their appropriate operation, control, and accurate simulation are essential. The simulation of WWTPs according to the process complexity has become an important issue in growing environmental awareness. In recent decades, artificial intelligence approaches have been used as effective tools in order to investigate environmental engineering issues. In this study, the effluent quality of Tabriz WWTP was assessed using two intelligence models, namely support Vector Machine (SVM) and artificial neural network (ANN). In this regard, several models were developed based on influent variables and tested via SVM and ANN methods. Three time scales, daily, weekly, and monthly, were investigated in the modeling process. On the other hand, since applied methods were sensitive to input variables, the Monte Carlo uncertainty analysis method was used to investigate the best-applied model dependability. It was found that both models had an acceptable degree of uncertainty in modeling the effluent quality of Tabriz WWTP. Next, ensemble approaches were applied to improve the prediction performance of Tabriz WWTP. The obtained results comparison showed that the ensemble methods represented better efficiency than single approaches in predicting the performance of Tabriz WWTP. HIGHLIGHTS SVM and FFNN methods were applied as alternatives to mathematical models to describe the behavior of WWTPs and deal with the complexity of the WWTP.; Daily, weekly, and monthly time scales were investigated in the modeling process.; The Monte Carlo method was used to evaluate the uncertainty of applied models.; The impact of ensemble approaches on improving the prediction performance was assessed.;
format	article
author	Nasim Hejabi Seyed Mahdi Saghebian Mohammad Taghi Aalami Vahid Nourani
author_facet	Nasim Hejabi Seyed Mahdi Saghebian Mohammad Taghi Aalami Vahid Nourani
author_sort	Nasim Hejabi
title	Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
title_short	Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
title_full	Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
title_fullStr	Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
title_full_unstemmed	Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
title_sort	evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/990119d14fb34a4a9df2d0f1b572f276
work_keys_str_mv	AT nasimhejabi evaluationoftheeffluentqualityparametersofwastewatertreatmentplantbasedonuncertaintyanalysisandpostprocessingapproachescasestudy AT seyedmahdisaghebian evaluationoftheeffluentqualityparametersofwastewatertreatmentplantbasedonuncertaintyanalysisandpostprocessingapproachescasestudy AT mohammadtaghiaalami evaluationoftheeffluentqualityparametersofwastewatertreatmentplantbasedonuncertaintyanalysisandpostprocessingapproachescasestudy AT vahidnourani evaluationoftheeffluentqualityparametersofwastewatertreatmentplantbasedonuncertaintyanalysisandpostprocessingapproachescasestudy
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Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study)

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