Authors: Ramhari Aghav, Somnath Mukherjee
Addresses: Civil Engineering Department, Environmental Engineering Division, Jadavpur University, Kolkata 700 032, West Bengal, India. ' Civil Engineering Department, Environmental Engineering Division, Jadavpur University, Kolkata 700 032, West Bengal, India
Abstract: The application of Artificial Neural Network (ANN) for the prediction of removal efficiency of resorcinol in water environment using low-cost carbonaceous adsorbents such as rice husk ash was studied in the present investigation. The input data used for training of the ANN model include adsorbent dose, adsorbate concentration, time of contact and pH. The various input variables were obtained in a laboratory experiment. The results obtained from ANN model for the prediction of resorcinol removal efficiency indicated that back-propagation ANN can be used for the modelling of batch adsorption kinetics.
Keywords: resorcinol adsorption; rice husk ash; modelling; artificial neural networks; ANNs; validation; water; resorcinol removal; modelling; batch adsorption kinetics.
International Journal of Environmental Technology and Management, 2011 Vol.14 No.1/2/3/4, pp.9 - 18
Published online: 29 Mar 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article