In addition to BPNN, RBFNN is another type of commonly deployed ANN, consisting of one input layer, one hidden layer and one output layer, see Fig. ). Instead of utilizing inputs and their associated weights like BPNN, RBFNN uses the distance between input and the centre for the learning process. At the hidden neuron, radially symmetric Gaussian basis function is commonly used as the activation function :