An artificial neural network combined with response surface methodology approach for modelling and optimization of the electro-coagulation for cationic dye

Abstract

An artificial neural network (ANN) approach with response surface methodology (RSM) technique has been applied to model and optimize the removal process of Brilliant Green dye by batch electrocoagulation process. A multilayer perceptron (MLP) - ANN model has been trained by four input neurons which represent the reaction time, current density, pH, NaCl concentration, and two output neurons representing the dye removal efficiency (%) and electrical energy consumption (kWh/kg). The optimized hidden layer neurons were obtained based on a minimum mean squared error. The batch electrocoagulation process was optimized using central composite design with RSM once the ANN network was trained and primed to anticipate the output. At optimized condition (electrolysis time 10 min, current density 80 A/m 2 , 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.

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B4C and Cr2O3 using RSM and ANN

“…The neural network developed is based on experimental results. The model training is performed using the experimental data and responses [30]. These were found to be a great advantage of the ANN model in obtaining the relative value of prediction [31].…”

Preparation of Bamboo-Based Activated Carbon via Steam Activation for Efficient Methylene Blue Dye Adsorption: Modeling and Mechanism Studies

“…Response surface methodology (RSM) is a mathematical and statistical method for modeling and analyzing problems with the influence of multiple variables. − Box–Behnken design (BBD) is one of the most commonly used design methods for RSM. , In this study, RSM and BBD were used to calculate the combination of process variables affecting MB removal. Initial MB concentration (150–200 mg/L), adsorption time (5–120 min), adsorbent dosage (30–50 mg), adsorption temperature (5–50 °C), and solution pH (3–11) were selected as adsorption variables (agitation speed = 100 rpm and volume of solution = 100 mL).…”

Differently Prepared PbO2/Graphitic Carbon Nitride Composites for Efficient Electrochemical Removal of Reactive Black 5 Dye

“…Reactive Black 5 (RB5) dye, or Remazol Black B (Scheme 1), belongs to the vinyl sulphone type of azo dyes. Azo dyes, aromatic compounds with one or more -N=N-groups, constitute the largest class of synthetic dyes in commercial application [1,2]. RB5 is most commonly used to dye cotton and other cellulosic fibers, wool, and nylon [3,4].…”

“…Different methods for degradation and removal of RB5 can be found in scientific literature, such as biodegradation and biocatalysis [1,10,11], photocatalysis [12][13][14][15], electrocoagulation [2], Fenton or Fenton-like reaction [6,16], adsorption [9], or by activation of peroxymonosulfate (PMS) [17,18].…”