Modeling of Nitrate Removal by Nanosized Iron Oxide Immobilized on Perlite Using Artificial Neural Network

摘要

The removal of nitrate from aqueous solution by adsorption process onto nanosized iron oxide immobilized on perlite (nIO-P) is novel, effective and easy way. In this work, the effective parameters on removal of nitrate by adsorption process, which included the amount of nIO-P(m), initial concentration of nitrate (C0), contact time, pH and temperature (T), were investigated. It was found that the content of adsorption followed decreasing order: m = 8>4>2>1g, C0 = 20>25>15> 10mgL~(-1), pH = 5 >7 > 8 >9 and T = 45 > 35 > 25 > 15 °C. The three-layered feed forward back propagation neural network was used for modeling of nitrate adsorption on nIO-P. The comparison between the predicted results of the designed artificial neural network (ANN) model and the experimental data proved that modeling of nitrate adsorption process using artificial neuron network was a good and precise method to predict the extent of adsorption of nitrate on adsorbent under different conditions.