Artificial Neural Network Based Prediction of Removal of Basic Dye from Its Aqueous Solution Using Activated Carbon
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 7
Abstract
Management of solid wastes and liquid effluents are a great menace and has become a formidable social problem. Many countries including India find it difficult to have a control on it. Disposal of highly coloured water and municipal solid waste is a problem for the municipal planners. In the present study an attempt has been made to convert putrescible vegetable waste into phosphoric acid activated carbon (PAAC) for the removal of methyl violet from its aqueous solution. Characterization of the activated carbon was done using various physico chemical methods and characterized with FT-IR, SEM EDAX and BET surface area analysis. Batch mode adsorption study was employed for studying the efficiency of PAAC to remove methyl violet from its aqueous solution. To optimize the study, a high quality representative model called artificial neural network (ANN) was employed using feed forward back propagation algorithm. A comparison of experimental and ANN data was done for the effect of pH, adsorbent dosage, initial dye concentration and time. It was found that the developed ANN model predicted the efficient adsorption of methyl violet onto PAAC.
Authors and Affiliations
Meena Sundari P, Meenambal T
Keywords
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