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Ali Amooey

Ali Amooey

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
Faculty: Faculty of Technology and Engineering
Address:
Phone: 01135305105

Research

Title
Modeling the Removal of Endosulfan from Aqueous Solution by Electrocoagulation Process Using Artificial Neural Network (ANN)
Type
JournalPaper
Keywords
Electrocoagulation
Year
2015
Journal industrial and engineering chemistry research
DOI
Researchers Seyed Mohammad Mirsoleimani-azizi ، Ali Amooey ، Shahram Ghasemi ، Saeid Salkhordeh-panbechouleh

Abstract

Electrocoagulation (EC) is an electrochemical method to treat polluted wastewaters and aqueous solutions. In this research, EC was used to remove Endosulfan from aqueous solution. The results show that the best conditions that obtained in this study are pH = 4, current density = 6.2 mA/cm 2 , initial concentration of Endosulfan = 30 mg/L, and electrolysis time = 60 min. The solution conductivity seems to have no significant effect on the removal efficiency. Artificial neural network (ANN) was utilized to model the experimental data. The model was developed by using three layer feed-forward neural network with eight neurons in the hidden layer for modeling of EC process. A comparison between the predicted results and experimental data gave high correlation coefficient (R 2 = 0.976) and showed that the model is able to predict the removal efficiency.