Modeling the removal of cadmium ions from aqueous solutions onto olive pips using neural network technique

Abstract EN

The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers.

Based on 112 batch experiments, pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05 temperature (20-60ºC) were studied.

The maximum uptake (=9 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlation The sensitivity analysis for outputs of ANN signified that the relative importance of initial pH equal to 38 % and it is the influential parameter in the treatment process, followed by initial concentration, agitation speed, biosorbent dosage, time and temperature.