earticle

영어

This study compared the performance of the FCM(C-Means)-based ANFIS(Adaptive Neuro-Fuzzy Inference System) model and the CFCM(Context-based Fuzzy C-Means) clustering-based ANFIS model. The FCM-ANFIS model sets the initial Fuzzy Rule through FCM clustering and optimizes the rule through neural network learning. The CFCM-ANFIS model generates more sophisticated rules through CFCM clustering that considers the input and output variable space and learns the neural network. As a result of the experiment, the verification RMSE of the FCM-based ANFIS model was 3.5654 when the number of clusters was 6, and the RMSE of the CFCM clustering-based ANFIS model was 3.3954 in the parameters (P = 6, C = 2), which was higher than the FCM-based ANFIS model. It was confirmed that the CFCM method had better prediction performance than the FCM method, and this study proved that the CFCM-based ANFIS model was more effective in predicting body fat percentage.