S. Tajmiri, E. Azimi, M.R. Hosseini, Y. Azimi, Evolving multilayer perceptron, and factorial design for modeling and optimization of dye decomposition by biosynthetized nano CdS diatomite composite, Environmental Research (2020) 182: 108997.

Design of experiment and hybrid genetic algorithm optimized multilayer perceptron (GA-MLP) artificial neural network have been employed to model and predict dye decomposition capacity of the biologically synthesized nano CdS diatomite composite. Impact of independent variables such as, light (UV: on-off), solution pH (5–8), composite weight (CW: 0.5–1 mg), initial dye concentration (DC: 10–20 mg/l) and contact time (0–120 min), mainly in two levels, were examined to evaluate dye removal efficiency of the composite. According to the developed response surface based on the factorial design, all independent variables shown positive interactive effect on dye removal (UV > CW > pH > DC), as well as the pH-CW mutual interaction, while both UV-DC and CW-DC had antagonistic effect. The pH-CW interaction was more influential than pH and DC. Incorporation of the intermediate measurements of dye removal …