Improving the robustness of recursive consequent parameters learning in evolving neuro-fuzzy systems
type: Item
instance of: scholarly article
title: Improving the robustness of recursive consequent parameters learning in evolving neuro-fuzzy systems
zbMATH Open document ID: 1475.68282
author: Edwin Lughofer
published in: Information Sciences
publication date: 2021-11-30T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 93C42
zbMATH DE Number: 7436256
zbMATH Keywords: evolving neuro-fuzzy systems
zbMATH Keywords: online data streams
zbMATH Keywords: recursive estimation of consequent parameters
zbMATH Keywords: recursive fuzzily weighted least squares (RFWLS)
zbMATH Keywords: multi-innovation RFWLS
zbMATH Keywords: recursive correntropy
zbMATH Keywords: recursive weighted total least squares (RWTLS)
describes a project that uses: PANFIS
describes a project that uses: ElemStatLearn
describes a project that uses: MOA
MaRDI profile type: Publication
full work available at URL: j.ins.2020.09.026
OpenAlex ID: W3087870029
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DOI: 10.1016/J.INS.2020.09.026
description: scientific article; zbMATH DE number 7436256