Design of local fuzzy models using evolutionary algorithms
type: Item
instance of: scholarly article
title: Design of local fuzzy models using evolutionary algorithms
zbMATH Open document ID: 1157.62515
author: P. P. Bonissone
author: Anil Varma
author: Kareem S. Aggour
author: Feng Xue
published in: Computational Statistics and Data Analysis
publication date: 2009-04-06T00:00:00Z
Mathematics Subject Classification ID: 62N99
Mathematics Subject Classification ID: 62P99
Mathematics Subject Classification ID: 62P30
zbMATH DE Number: 5540428
zbMATH Keywords: fuzzy models
zbMATH Keywords: evolutionary algorithms
zbMATH Keywords: instance-based models
zbMATH Keywords: similarity measures
zbMATH Keywords: prediction
MaRDI profile type: Publication
full work available at URL: j.csda.2006.04.013
OpenAlex ID: W1990164106
cites work: Q3157502
cites work: Can fuzzy neural nets approximate continuous fuzzy functions?
cites work: Q5687949
cites work: Data mining and knowledge discovery with evolutionary algorithms
cites work: Q3838055
cites work: Q3685836
cites work: An experiment in linguistic synthesis with a fuzzy logic controller
cites work: Continuous case-based reasoning
cites work: Q4218007
cites work: Q5526189
cites work: Q4446523
cites work: Fuzzy identification of systems and its applications to modeling and control
cites work: Automatic Generation of Neural Network Architecture Using Evolutionary Computation
cites work: Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
DOI: 10.1016/J.CSDA.2006.04.013
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description: scientific article; zbMATH DE number 5540428