The ANN created is able to calculate the dosage based on the value of initial turbidity of the fluid to be treated with a MSE 0 mg/L, achieving removal percentages greater than 93% for most cases.
Index Terms—Aluminum sulfate (Al2(SO4)3 18H2O), artificial neural networks, coagulation, flocculation, optimal dosage of coagulant.
A. J. León-Luque and C. L. Barajas G. are with the Faculty of Environmental Engineer, Santo Tomás Univeristy, Bogotá, Colombia (email: andrea.leon@usantotomas.edu.co, claudia.barajas@usantotomas.edu.co).
C. A. Peña-Guzmán is with the Department of Environmental Engineer, Faculty of Engineer, Santo Tomás Univeristy and Universidad Autónoma de Colombia, Bogotá, Colombia (e-mail: carlos.pena@usantotomas.edu.co, carpeguz@gmail.com).
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Cite: A. J. León-Luque, C. L. Barajas, and C. A. Peña-Guzmán, "Determination of the Optimal Dosage of Aluminum Sulfate in the Coagulation-Flocculation Process Using an Artificial Neural Network," International Journal of Environmental Science and Development vol. 7, no. 5, pp. 346-350, 2016.