Fuzzy Inference Methods Employing T-norm with Threshold and Their Implementation

Bui Cong Cuong; Nguyen Hoang Phuong; Ho Khanh Le; Bui Truong Son; Koichi Yamada

doi:10.20965/jaciii.2003.p0362

single-jc.php

« previous

JACIII Vol.7 No.3 pp. 362-369

doi: 10.20965/jaciii.2003.p0362

(2003)

Paper:

Views over last 60 days: 293

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, 2003

Accepted:

August 26, 2003

Published:

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:

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****

Bui Cong Cuong^*, Nguyen Hoang Phuong^**, Ho Khanh Le^, Bui Truong Son^, and Koichi Yamada^**