Innovative binary sorption of Cobalt(II) and methylene blue by Sargassum latifolium using Taguchi and hybrid artificial neural network paradigms

Abstract

The present investigation has been designed by Taguchi and hybrid artificial neural network (ANN) paradigms to improve and optimize the binary sorption of Cobalt(II) and methylene blue (MB) from an aqueous solution, depending on modifying physicochemical conditions to generate an appropriate constitution for a highly efficient biosorption by the alga; Sargassum latifolium. Concerning Taguchi's design, the predicted values of the two responses were comparable to actual ones. The biosorption of Cobalt(II) ions was more efficient than MB, the supreme biosorption of Cobalt(II) was verified in run L21 (93.28%), with the highest S/N ratio being 39.40. The highest biosorption of MB was reached in run L22 (74.04%), with a S/N ratio of 37.39. The R2 and adjusted R2 were in reasonable values, indicating the validity of the model. The hybrid ANN model has exclusively emerged herein to optimize the biosorption of both Cobalt(II) and MB simultaneously, therefore, the ANN model was better than the Taguchi design. The predicted values of Cobalt(II) and MB biosorption were more obedience to the ANN model. The SEM analysis of the surface of S. latifolium showed mosaic form with massive particles, as crosslinking of biomolecules of the algal surface in the presence of Cobalt(II) and MB. Viewing FTIR analysis showed active groups e.g., hydroxyl, α, β-unsaturated ester, α, β-unsaturated ketone, N–O, and aromatic amine. To the best of our knowledge, there are no reports deeming the binary sorption of Cobalt(II) and MB ions by S. latifolium during Taguchi orthogonal arrays and hybrid ANN.

Exclusive Biosynthesis of Pullulan Using Taguchi’s Approach and Decision Tree Learning Algorithm by a Novel Endophytic Aureobasidium pullulans Strain

“…The Taguchi method was utilized to find the best conditions to enhance the pullulan biosynthesis process. Its orthogonal array design allowed for the efficient development of optimal conditions using the lowest number of trials, thereby saving both time and effort [ 15 , 17 ]. The orthogonal arrays of the seven control factors and the corresponding pullulan biosynthesis laboratory data of the 27 trials are presented in Table 1 .…”

“…It is a straightforward and organized approach for finding the optimal level of each factor while maximizing the response with a limited number of experimental runs on multiple variables [ 15 , 16 ]. The Taguchi method originated from expanded factorial and Latin squares (L) designs, known as orthogonal arrays, which are matrices where every pair of columns contains the same number of each possible pair of factors [ 16 , 17 ].…”

“…This is what differentiates the Taguchi method from traditional statistical techniques. Taguchi categorizes the S/N ratio into three types, i.e., nominal is better, larger is better, and smaller is better, depending on the desired response [ 15 , 17 ]. The S/N ratio replaces the response in determining the optimal control factor levels and disregards variations caused by uncontrollable conditions [ 15 ].…”

Pseudomonas alcaliphila NEWG-2 as biosorbent agent for methylene blue dye: optimization, equilibrium isotherms, and kinetic processes

“…Taguchi is designed to control the noise (uncontrollable) factors during experimentation to force identify optimal control factors settings that cause the operating conditions to resist the variation caused by the noise factors. So, a high S/N ratio signifies that the control factors are at their optimal and the minimal effect of the noise factors 43 .…”

“…Therefore, the operating conditions that minimize the process variability (standard deviation) are accompanied by increasing the S / N ratio, where the S/ N ratio detects the variance between the predictable (desired) value and the experimental response. Therefore, the S/N ratio directs the response to the optimum circumstances of control (signal) variables, consequently, ignored the deviations occured by the uncontainable (noise) factors 31 , 35 .…”