Derivation of fuzzy membership functions using one-dimensional self-organizing maps

Author

Sandidge, Thomas E. ; Dagli, Cihan H.

Author_Institution

Smart Eng. Syst. Lab., Missouri Univ., Rolla, MO, USA

Volume

2

fYear

1997

fDate

12-15 Oct 1997

Firstpage

995

Abstract

This paper discusses a system of self-organizing maps that approximate the fuzzy membership function for an arbitrary number of fuzzy classes. This is done through the ordering and clustering properties of one-dimensional self-organizing maps and iterative approximation of conditional probabilities of nodes in one map being the winner given that a node in the other map is the winner. Application of this system reduces fuzzy membership design time to that required to train the system of self-organizing maps

Keywords

function approximation; fuzzy set theory; iterative methods; learning (artificial intelligence); probability; self-organising feature maps; 1D self-organizing maps; conditional probability; function approximation; fuzzy membership functions; iterative method; learning; Encoding; Equations; Fuzzy systems; Input variables; Laboratories; Neurons; Research and development management; Self organizing feature maps; Systems engineering and theory; Wastewater treatment;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1062-922X

Print_ISBN

0-7803-4053-1

Type

conf

DOI

10.1109/ICSMC.1997.638077

Filename

638077