Central composite design (CCD) and artificial neural network-based Levenberg–Marquardt algorithm (ANN–LMA) for the extraction of lanasyn black by cloud point extraction Scientific paper
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Abstract
The lanasyn black is among the most often used in manufacturing and is challenging to take out during the treatment of wastewaters from textile industry. The cloud point extraction was used for their elimination from an aqueous solution. The multivariable process parameters have been independently optimized using the central composite design and the Levenberg–Marquardt algorithm-based artificial neural network for the highest yield of the extraction of lanasyn black via the cloud point extraction. The CCD forecasts the output maximum of 97.01 % under slightly altered process parameters. Still, the ANN–LMA model predicts the extraction yield (99.98 %) using 1.04 g of KNO3, the beginning pH of solution 8.99, the initial content of lanasyn black 24.57 ppm and 0.34 mass % of Triton X-100. With the coefficients of determination of 0.997 and 0.9777, the most recent empirical verification of the model mentioned above predictions using CCD and ANN–LMA is determined to be satisfactory.
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