A proposal of fuzzy modeling on fusion axes considering the data structure

Author

Yamamoto, Kosuke ; Yoshikawa, Tomohiro ; Furuhashi, Takeshi

Author_Institution

Dept. of Electr. & Electron. Eng., Mie Univ., Japan

Volume

1

fYear

2003

Firstpage

348

Abstract

Fuzzy modeling is known as one of the effective methods to identify unknown non-linear input-output relationships. In gathering information from constructed models or constructing models from known information, the model\´s understandability becomes essential. This paper defines new axes by fitting distributed data in input space and proposes a fuzzy modeling method considering data structure. This paper calls these axes, "fusion axes". The effectiveness of the proposed method is shown through some numerical experiments.

Keywords

data structures; fuzzy set theory; identification; maximum entropy methods; modelling; pattern clustering; principal component analysis; regression analysis; data clustering; data structure; distributed data fitting; fusion axes; fuzzified multiple discriminant analysis; fuzzy C-means; fuzzy modeling; maximum entropy; principal component axes; understandability of rules; unknown nonlinear input-output relationships; Computer networks; Data mining; Data structures; Feature extraction; Input variables; Laboratories; Microwave integrated circuits; Neural networks; Pattern recognition; Proposals;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on

Print_ISBN

0-7803-7810-5

Type

conf

DOI

10.1109/FUZZ.2003.1209387

Filename

1209387