Extending the dynamic range of the determination of copper by adsorption differential pulse stripping method using a principal component artificial neural network

A principal component artificial neural network (PC-ANN) has been applied for the analysis of the voltammogram data of Cu(II) and Cu(II)–PAN complex for extending the dynamic range of the determination of Cu(II) (5–550 μg/l). A three layer back-propagation network (6:5:1) was used with learning rate (r=0.09) and momentum (m=0.9), with sigmoidal transfer function in the hidden layer and one bias node in the input layer. Overall, the application of PC-ANN enables the extension of the dynamic range of the determination of Cu(II) from its narrow linear range (5–50 μg/l) to the high dynamic range (5–550 μg/l).