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Fuzzy Inference Methods Employing T-norm with Threshold and Their Implementation
Bui Cong Cuong*, Nguyen Hoang Phuong**, Ho Khanh Le*, Bui Truong Son***, and Koichi Yamada****
*Institute of Mathematics, National Center of Natural Science and Technology, 18 Hoang Quoc Viet Rd., 10307 Hanoi, Vietnam
**Institute of Information Technology, National Center of Natural Science and Technology, 18 Hoang Quoc Viet Rd., Cau Giay, Dist., Hanoi, Vietnam
***Post and Telecommunication Institute of Technology, 122 Hoang Quoc Viet Rd. Cau Giay Dist., Hanoi, Vietnam
****Dept. of Management and Information Systems Science, Nagaoka University of Technology, 1603-1, Kami-tomioka, Nagaoka, Niigata, 904-2188, Japan
Received:June 30, 2003Accepted:August 26, 2003Published:October 20, 2003
Keywords:fuzzy inference system, inference method, fuzzy rule, t-norm with threshold
Abstract
The fuzzy inference engine is an important part of reasoning systems. Among the many different types of inference, MATLAB is a powerful tool including many useful toolboxes, one of which is the Fuzzy Logic Toolbox. To improve toolbox capacity, we programmed and installed several new inference methods.
Cite this article as:B. Cuong, N. Phuong, H. Le, B. Son, and K. Yamada, “Fuzzy Inference Methods Employing T-norm with Threshold and Their Implementation,” J. Adv. Comput. Intell. Intell. Inform., Vol.7 No.3, pp. 362-369, 2003.Data files: