Neural network modeling of biotreatment of triphenylmethane dye solution by a green macroalgae

Abstract The potential of a green macroalgae Cladophora species was investigated as a viable biomaterial for biotreatment of Malachite Green (MG) solution. The effects of operational parameters such as temperature, pH, initial dye concentration, reaction time and amount of algae on biological decolorization efficiency were studied. Biotreatment of MG solution by live and dead algae was compared. The reusability and efficiency of the live algae in long-term repetitive operations were also examined. COD and FT-IR analysis revealed the ability of algal species in biological degradation of the dye. An artificial neural network (ANN) model was developed to predict the biotreatment of MG solution. The findings indicated that the ANN provided reasonable predictive performance ( R 2  = 0.987). The influence of each parameter on the variable studied was assessed, and reaction time and initial pH were found to be the most significant factors, followed by temperature, initial dye concentration and amount of algae. Simulations based on the developed ANN model can estimate the behavior of the biological biotreatment process under different conditions.

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