An efficient tuning method for designing a fuzzy inference model

Author

Huang, Yc-Ping ; Yu, Shin-Hway ; Horng, Maw-Sheng

Author_Institution

Dept. of Comput. Sci. & Eng., Tatung Univ., Taipei, Taiwan

Volume

1

fYear

2001

fDate

2001

Firstpage

1

Abstract

A novel fast tuning algorithm is proposed to expedite the converging process in the parameter identification of fuzzy models. In order to improve the disadvantages of the time-consuming gradient descent method, the principle of this new algorithm is only to tune the consequent parts of the fuzzy rules. The membership functions of the fuzzy model remain unchanged. The proposed tuning method is applicable to two different types of fuzzy rules. Some simulation results are given to verify that the proposed method can converge speedily and have better inference capability than conventional methods

Keywords

fuzzy logic; fuzzy set theory; inference mechanisms; parameter estimation; uncertainty handling; converging process; fast tuning algorithm; fuzzy inference model design; fuzzy model; fuzzy rules; gradient descent method; inference capability; membership functions; parameter identification; tuning method; Buildings; Computer science; Design methodology; Electronic mail; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Inference algorithms; Parameter estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 2001 IEEE International Conference on

Conference_Location

Tucson, AZ

ISSN

1062-922X

Print_ISBN

0-7803-7087-2

Type

conf

DOI

10.1109/ICSMC.2001.969778

Filename

969778