Combination of the artificial neural network and advection-dispersion equation for modeling of methylene blue dye removal from aqueous solution using olive stones as reactive bed

In the present investigation, the propensity of olive stones (OS) to be utilized in the removal of methylene blue dye (MBD) from polluted water was analyzed. The three-layer artificial neural network (ANN) model has been used as an alternative method in fixing the relationship describing the sorption process accurately and matching with the experimental results. Therefore, 137 batch experiments were performed for characterizing the equilibrium sorption properties. Applying the ANN model proved that the contact time was the most influential parameter. Subsequently, the transport of methylene blue dye through the OS bed was described by integrating the ANN model with the advection–dispersion equation which describes the transport of contaminant in the porous medium resulting in a good agreement between expected and measured results with a correlation coefficient (R) greater than 0.9789.