A self-organizing neural fuzzy inference network

Author

Castellano, G. ; Fanelli, A.M.

Author_Institution

Dipt. di Inf., Bari Univ., Italy

Volume

5

fYear

2000

fDate

2000

Firstpage

14

Abstract

A self-organizing neural network is proposed which is inherently a fuzzy inference system with the capability of learning fuzzy rules from data. The learning strategy consists of two phases: a self-organizing clustering to establish the structure of the network as well as the initial values of its parameters and a supervised learning phase for optimal adjustment of these parameters. After learning, the network encodes in its structure the essential design parameters of a fuzzy system. An example is given to illustrate the characteristics and capabilities of the proposed network

Keywords

fuzzy neural nets; inference mechanisms; learning (artificial intelligence); self-organising feature maps; fuzzy inference system; learning fuzzy rules; learning strategy; self-organizing clustering; self-organizing neural network; Data mining; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Inference mechanisms; Input variables; Network topology; Neural networks; Supervised learning; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on

Conference_Location

Como

ISSN

1098-7576

Print_ISBN

0-7695-0619-4

Type

conf

DOI

10.1109/IJCNN.2000.861428

Filename

861428