“…The input layer can be represented by a vector x ¼ x 1 ,x 2 , … ,x M ½ , the output layer represented by a vector y ¼ y 1 ,y 2 , … ,y K ÂÃ , and the activation function of hidden layer is the wavelet basis function. The output Y j can be given as follows [11,19]: where, j ¼ 1, 2, 3, … , K; M is the number of inputs; K is the number of output layers; N is the number of hidden layers; g is the bias; and σ u ðÞ is the activation function of the output layer, the most common formula of activation function being sigmoid function which can be illustrated as follows [12]:…”