Modeling of Ammonium and COD Adsorption in Aqueous Solutions Using an Artificial Neural Network

Abstract

This paper illustrates the application of the artificial neural network for adsorption of ammonium NH4 and COD from fish farm by rice straw as low cost carbonaceous. The effects of input parameters (contact time, pH, initial concentration of NH4 and COD, adsorbent dosages, and temperature) are studied to optimize the conditions for maximum removal of NH4 and COD. The artificial neural network with a single hidden layer with ten nodes trained with Levenberg-Marquardt algorithm predicted the removal efficiency of NH4 and COD from aqueous solution accurately.