A New Fuzzy Inference System with the aid of SAHN based algorithm

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 of Jenkins´s gas furnace data and Sugeno´s non-linear process data.