Abstract
In this study, an artificial neural network (ANN) based techniques is applied for the prediction of the percentage removal of Cr(VI) ions from aqueous solution using eight different natural biosorbents. The effects of operating parameters such as initial pH, initial Cr(VI) ion concentration, adsorbent dosages, and contact time are studied to optimize the conditions for maximum removal of Cr(VI) ions. The ANN with a single hidden layer trained with Levenberg-Marquardt algorithm predicted the percentage removal of Cr(VI) ions from aqueous solution accurately.
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