Fig. 1.

Detailed diagram of the neural network structure. The neural network consists of 11 nodes in one input layer, 5 nodes in one hidden layer, and 1 node in one output layer. The parameters × 1– × 11, w, b, n, and y1 refer to the inputs, weight, deviation (i.e., a measure of the difference between the predictions of our model and the actual values), node in the hidden layer, and output, respectively. Full connection mode was adopted for the neural network. A sigmoid activation function was used for each layer