j sayyad amin - Chemical Engineering department, University of Guilan, Rasht ۴۱۶۳۵- ۳۷۵۶, IRAN
h heshmati - Chemical Engineering department, University of Guilan, Rasht ۴۱۶۳۵- ۳۷۵۶, IRAN

In this study, Artificial Neural Network (ANN) was developed to predict adsorption and removal percent of some metal ions on activated carbon prepared from apricot stone (ASAC). The ANN which was used, is a perceptron feed forward network that has two layers with 10 and 1 neuron(s) in the first and second layer, respectively. According to reported errors, the estimated/predicted values of ANN had a good agreement with experimental data.

Adsorption, Neural Network, Removal percent, Metal ions