Modeling of Cu2+ adsorption onto powder activated carbon using artificial neural network

Monitoring the content of Cu2+ plays an important role in the analysis of surface, drinking and wastewaters because it is harmful for health of human. The removal of Cu2+ from aqueous solution by adsorption process onto powder activated carbon is effective and easy way. Artificial neural network modeling has been successfully used to investigate the cause effect relationship in the adsorption process. The artificial neural network model could describe the behavior of the complex interaction process with the range of experimental conditions adopted [1]. Simulation based on the artificial neural network model can estimate the behavior of the process under different conditions.