Optimal Fuzzy Models with the Aid of SAHN-based Algorithm
Jong‐Seok Lee, Kyung‐Won Jang, Tae-Chon Ahn · International Journal of Fuzzy Logic and Intelligent Systems · 2006
In this paper, we have presented a Sequential Agglomerative Hierarchical Nested (SAHN) algorithm-based data clustering method in fuzzy inference system to achieve optimal performance of fuzzy model. SAHN-based algorithm is used to give possible range of number of clusters with cluster centers for the system identification. The axes of membership functions of this fuzzy model are optimized by using cluster centers obtained from clustering method and the consequence parameters of the fuzzy model are identified by standard least square method. Finally, in this paper, we have observed our model's output performance using the Box and Jenkins's gas furnace data and Sugeno's non-linear process data.