Genetic algorithm and artificial neural network model for prediction of discoloration dye from an electro-oxidation process in a press-type reactor

Author:

Picos Alain1,Peralta-Hernández Juan M.1

Affiliation:

1. Departamento de Química, División de Ciencias Naturales y Exactas, Campus Guanajuato. Universidad de Guanajuato, Guanajuato, Gto. 36050, México

Abstract

Abstract This study evaluates the effectiveness of an artificial neural network-genetic algorithm (ANN-GA) artificial intelligence (AI) model in the prediction of behavior and optimization of an electro-oxidation pilot press-type reactor, which treats a synthetic wastewater prepared with a dye. The ANN was built from real experimental data using as input the following variables: time, flow, j, dye concentration, and as output discoloration. The performance of the ANN was measured with MAPE (8.3868%), calculated from real and predicted values. The coupled AI model was used to find the best operational conditions: discoloration efficiency (above 90%) at j = 27 mA/cm2 and dye concentration of 230 mg/L.

Publisher

IWA Publishing

Subject

Water Science and Technology,Environmental Engineering

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