Neural network modeling of Pb2+ removal from wastewater using electrodialysis

Artificial neural network (ANN) was applied to predict separation percent (SP) of lead ions from wastewater using electrodialysis (ED). The aim was to predict SP of Pb2+ as a function of concentration, temperature, flow rate and voltage. Optimum numbers of hidden layers and nodes in each layer were determined. The selected structure (4:6:2:1) was used for prediction of SP of lead ions as well as current efficiency (CE) of ED cell for different inputs in the domain of training data. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values.