ANFIS is a type of machine learning algorithm which combines neural networks, fuzzy logic and inference system . A typical ANFIS network structure consists of five layers: fuzzy layer, product layer, normalization layer, defuzzification layer and summation layer , see Fig. . This method integrates the learning from both neural network and fuzzy logic, thereby exhibiting enhanced robustness . The first layer (fuzzy layer) maps input values within the range of 0-1 based on fuzzy membership functions. In the second layer, the weights of each membership function are evaluated by processing all input signals. The third layer (normalization layer) computes the ratio of the firing strength of each rule to the total firing strength of all rules, resulting in the normalized firing strength. The fourth layer handles defuzzification, generating output based on the inference of rules. Each node in this layer is adaptive, with a corresponding node function. Finally, the fifth layer, consisting of a single node, sums all input signals from the previous layer to produce the result.