The network parameters obtained in the optimization process are summarized in Table 1, the meaning of which is as follows: IL - number of neurons in the input layer; HL - number of neurons in the hidden layer; OL - number of neurons in the output layer; TF - activation function of hidden and output layer neurons, respectively; DDF - function of dividing input-target data into training and validation data; PF - network error calculation function; MN - maximum number of neurons in the hidden layer; spread – neuron’s spread width; goal - the smallest MSE target value; RBF - radial basis transfer function (radbas); linear - linear transfer function (purelin); MSE - mean squared error; dividerand - random division of input-target data.