Rule-based fuzzy neural networks realized with the aid of linear function Prototype-driven fuzzy clustering and layer Reconstruction-based network design strategy

In this study, we introduce novel fuzzy neural networks designed with the aid of linear function prototype-driven fuzzy clustering (LFPFC) and layer reconstruction-based network design strategy to deal with the regression problem. The LFPFC constitutes a new clustering technique inspired by the fuzz...

Full description

Bibliographic Details

Published in:	Expert systems with applications Vol. 219; p. 119655
Main Authors:	Park, Sang-Beom, Oh, Sung-Kwun, Kim, Eun-Hu, Pedrycz, Witold
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.06.2023
Subjects:	Distance-based LFPFC Estimated output-based LFPFC Fuzzy c-regression model (FCRM) clustering Layer reconstruction-based network design strategy Linear function prototype-driven fuzzy clustering (LFPFC) Distance-based LFPFC Estimated output-based LFPFC Linear function prototype-driven fuzzy clustering (LFPFC) Layer reconstruction-based network design strategy Fuzzy c-regression model (FCRM) clustering
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!