Application of artificial neural network and genetic algorithm to modeling and optimization of removal of methylene blue using activated carbon

The activated carbon (AC) prepared from low cost available source (peanut sticks) were identified with various techniques such as FT-IR and SEM analysis. The influence of variables was simulated using artificial neural network (ANN) subsequent of application of genetic algorithm (GA) for the optimization of effective variables. The adsorption kinetics was modeled via the trained ANN as fitness function with acceptable accuracy of ADD = 1.65% and R2 = 0.998. Following application of hybrid ANN-GA under the optimal operating conditions, maximum dye removal (96.2%) has been achieved.