An artificial neural network combined with response surface methodology approach for modelling and optimization of the electro-coagulation for cationic dye
Manisha S. Kothari, Kinjal G. Vegad, Kosha A. Shah, Ashraf Aly Hassan
Abstract
, initial pH 5 and electrolyte NaCl concentration 0.5 g/L), RSM projected decolorization of 98.83% and electrical energy consumption of 14.99 kWh/kg. This study shows that the removal of brilliant green dye can be successfully carried out by a batch electrocoagulation process. Therefore, the process is successfully trained by ANN and optimized by RSM for similar applications.
Topics & Concepts
Response surface methodologyElectrocoagulationArtificial neural networkCentral composite designMultilayer perceptronElectrolysisMaterials scienceElectrolyteCoagulationMean squared errorPerceptronProcess (computing)Biological systemProcess engineeringChromatographyComputer scienceChemistryMathematicsArtificial intelligenceEnvironmental scienceEnvironmental engineeringEngineeringElectrodeStatisticsPsychologyPsychiatryBiologyPhysical chemistryOperating systemWater Quality Monitoring and AnalysisAdsorption and biosorption for pollutant removalAdvanced oxidation water treatment