Investigation of Artificial Intelligence Approaches Capability in Predicting the Wastewater Treatment Plant Performance (Case Study: Tabriz Wastewater Treatment Plant)

Document Type : Research Article


1 Department of Water Engineering , Faculty of civil Engineering, University of Tabriz

2 Department of Water Engineering, Faculty of Civil, University of Tabriz, Tabriz, Iran

3 Department of Civil Engineering, Ahar Branch, Islamic Azad University – Ahar - Iran


Due to the excessive concern about environmental issues, researchers had to come up with a better solution to control the Wastewater treatment plants (WWTPs).In this research, two approaches, including Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been used for modeling the effluent quality of the Tabriz Wastewater Treatment Plant. Input data of models consist ofBODinf, CODinf, TSSinf, and PHinf of influent sewage related to Tabriz Treatment Plant which has been used to predict the corresponding value of BODeff, CODeff, and TSSeff concerning the treatment plant effluent. The daily, weekly, and monthly average data have been studied. According to the results, the two approaches mentioned, have the best performance in the prediction of the monthly average dataset of effluent parameters of Tabriz Wastewater Treatment Plant.


Main Subjects

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