Title :
A New Fuzzy Inference System with the aid of SAHN based algorithm
Author :
Kyungwon Jang ; Zhongxian Wang ; Taechon Ahn
Author_Institution :
Wonkwang Univ., Ik-San, South Korea
Abstract :
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.
Keywords :
fuzzy reasoning; least squares approximations; optimisation; pattern clustering; Box of Jenkins gas furnace data; Sugeno nonlinear process data; data clustering; fuzzy inference system; least square method; membership function; sequential agglomerative hierarchical nested algorithm; system identification; Clustering algorithms; Clustering methods; Furnaces; Fuzzy control; Fuzzy reasoning; Fuzzy systems; Inference algorithms; Least squares methods; Parameter estimation; System identification; Fuzzy inference system; Membership function; SAHN (Sequential Agglomerative Hierarchical Nested) based algorithm; Standard least square method; System identification;
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
DOI :
10.1109/CHICC.2006.280609
