Cover Image

A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function

In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized regression neural network (GRNN). It is an enhanced version of the GRNN, which pr...

Full description

Saved in:
Bibliographic Details
Main Authors: Yap K.S., Lim C.P., Abidin I.Z.
Other Authors: 24448864400
Format: Article
Published: 2023
Subjects:
Adaptive resonance theory (ART)
Bayesian theorem
Generalized regression neural network (GRNN)
Online sequential extreme learning machine
Algorithms
Artificial Intelligence
Computer Simulation
Models, Theoretical
Neural Networks (Computer)
Online Systems
Pattern Recognition, Automated
Arts computing
E-learning
Education
Feedforward neural networks
Food processing
Image classification
Internet
Learning systems
Radial basis function networks
Resonance
Time series analysis
algorithm
article
artificial intelligence
artificial neural network
automated pattern recognition
computer simulation
methodology
online system
theoretical model
Adaptive resonance theories
Adaptive resonance theory
Empirical studies
Extreme Learning Machine
Gaussian
Generalized regression neural network
Hybrid model
Loss functions
Neural network modelling
On-line learning
Radial basis function neural networks
Sequential learning
Time-series prediction
Neural networks
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-30951
record_format dspace
spelling my.uniten.dspace-309512023-12-29T15:56:28Z A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function Yap K.S. Lim C.P. Abidin I.Z. 24448864400 55666579300 35606640500 Adaptive resonance theory (ART) Bayesian theorem Generalized regression neural network (GRNN) Online sequential extreme learning machine Algorithms Artificial Intelligence Computer Simulation Models, Theoretical Neural Networks (Computer) Online Systems Pattern Recognition, Automated Arts computing E-learning Education Feedforward neural networks Food processing Image classification Internet Learning systems Radial basis function networks Resonance Time series analysis algorithm article artificial intelligence artificial neural network automated pattern recognition computer simulation methodology online system theoretical model Adaptive resonance theories Adaptive resonance theory Adaptive resonance theory (ART) Bayesian theorem Empirical studies Extreme Learning Machine Gaussian Generalized regression neural network Generalized regression neural network (GRNN) Hybrid model Loss functions Neural network modelling On-line learning Online sequential extreme learning machine Radial basis function neural networks Sequential learning Time-series prediction Neural networks In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized regression neural network (GRNN). It is an enhanced version of the GRNN, which preserves the online learning properties of adaptive resonance theory (ART). A series of empirical studies to assess the effectiveness of GART in classification, regression, and time series prediction tasks is conducted. The results demonstrate that GART is able to produce good performances as compared with those of other methods, including the online sequential extreme learning machine (OSELM) and sequential learning radial basis function (RBF) neural network models. � 2008 IEEE. Final 2023-12-29T07:56:28Z 2023-12-29T07:56:28Z 2008 Article 10.1109/TNN.2008.2000992 2-s2.0-52149111368 https://www.scopus.com/inward/record.uri?eid=2-s2.0-52149111368&doi=10.1109%2fTNN.2008.2000992&partnerID=40&md5=7f6585894e735f5e16eeedbcc15ed951 https://irepository.uniten.edu.my/handle/123456789/30951 19 9 1641 1646 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Adaptive resonance theory (ART)
Bayesian theorem
Generalized regression neural network (GRNN)
Online sequential extreme learning machine
Algorithms
Artificial Intelligence
Computer Simulation
Models, Theoretical
Neural Networks (Computer)
Online Systems
Pattern Recognition, Automated
Arts computing
E-learning
Education
Feedforward neural networks
Food processing
Image classification
Internet
Learning systems
Radial basis function networks
Resonance
Time series analysis
algorithm
article
artificial intelligence
artificial neural network
automated pattern recognition
computer simulation
methodology
online system
theoretical model
Adaptive resonance theories
Adaptive resonance theory
Adaptive resonance theory (ART)
Bayesian theorem
Empirical studies
Extreme Learning Machine
Gaussian
Generalized regression neural network
Generalized regression neural network (GRNN)
Hybrid model
Loss functions
Neural network modelling
On-line learning
Online sequential extreme learning machine
Radial basis function neural networks
Sequential learning
Time-series prediction
Neural networks
spellingShingle Adaptive resonance theory (ART)
Bayesian theorem
Generalized regression neural network (GRNN)
Online sequential extreme learning machine
Algorithms
Artificial Intelligence
Computer Simulation
Models, Theoretical
Neural Networks (Computer)
Online Systems
Pattern Recognition, Automated
Arts computing
E-learning
Education
Feedforward neural networks
Food processing
Image classification
Internet
Learning systems
Radial basis function networks
Resonance
Time series analysis
algorithm
article
artificial intelligence
artificial neural network
automated pattern recognition
computer simulation
methodology
online system
theoretical model
Adaptive resonance theories
Adaptive resonance theory
Adaptive resonance theory (ART)
Bayesian theorem
Empirical studies
Extreme Learning Machine
Gaussian
Generalized regression neural network
Generalized regression neural network (GRNN)
Hybrid model
Loss functions
Neural network modelling
On-line learning
Online sequential extreme learning machine
Radial basis function neural networks
Sequential learning
Time-series prediction
Neural networks
Yap K.S.
Lim C.P.
Abidin I.Z.
A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function
description In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized regression neural network (GRNN). It is an enhanced version of the GRNN, which preserves the online learning properties of adaptive resonance theory (ART). A series of empirical studies to assess the effectiveness of GART in classification, regression, and time series prediction tasks is conducted. The results demonstrate that GART is able to produce good performances as compared with those of other methods, including the online sequential extreme learning machine (OSELM) and sequential learning radial basis function (RBF) neural network models. � 2008 IEEE.
author2 24448864400
author_facet 24448864400
Yap K.S.
Lim C.P.
Abidin I.Z.
format Article
author Yap K.S.
Lim C.P.
Abidin I.Z.
author_sort Yap K.S.
title A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function
title_short A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function
title_full A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function
title_fullStr A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function
title_full_unstemmed A hybrid ART-GRNN online learning neural network with a ?-insensitive loss function
title_sort hybrid art-grnn online learning neural network with a ?-insensitive loss function
publishDate 2023
_version_ 1806423361208713216
score 13.222552

Similar Items