An interval fuzzy model using a fuzzy neural network

Author

Hashiyama, Tomonori ; Furuhashi, Takeshi ; Uchikawa, Yoshiki

Author_Institution

Dept. of Electron.-Mech. Eng., Nagoya Univ., Japan

Volume

2

fYear

1992

fDate

7-11 Jun 1992

Firstpage

745

Abstract

The authors propose a model of human decision making, based on fuzzy inference whose consequences are described with weighted linear equations. In this model, the input space is divided into fuzzy sub-spaces, and the input-output relationships are identified with a weighted linear equation in each sub-space. The new fuzzy neural network (FNN) identifies the upper side and lower side of the interval fuzzy model. From the identified model, it is easy to determine which attributes mainly give positive/negative evaluations of the objects. Experiments were conducted using face graphs to show the feasibility of the new model and the new FNN

Keywords

fuzzy logic; inference mechanisms; neural nets; pattern recognition; psychology; visual perception; face graphs; fuzzy inference; fuzzy neural network; human decision making; inference mechanisms; input-output relationships; interval fuzzy model; pattern recognition; psychology; visual perception; weighted linear equations; Blades; Decision making; Face; Fuzzy neural networks; Humans; Multi-layer neural network; Neural networks; Nonlinear equations; Regression analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1992. IJCNN., International Joint Conference on

Conference_Location

Baltimore, MD

Print_ISBN

0-7803-0559-0

Type

conf

DOI

10.1109/IJCNN.1992.226898

Filename

226898