A survey of adaptive resonance theory neural network models for engineering applications

Leonardo Enzo Brito da Silva; Islam Elnabarawy; Donald C. Wunsch

doi:10.1016/j.neunet.2019.09.012

A survey of adaptive resonance theory neural network models for engineering applications

Leonardo Enzo Brito da Silva
, Islam Elnabarawy
, Donald C. Wunsch

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	167-203
Number of pages	37
Journal	Neural Networks
Volume	120
DOIs	https://doi.org/10.1016/j.neunet.2019.09.012
State	Published - Dec 2019

ASJC Scopus Subject Areas

Cognitive Neuroscience
Artificial Intelligence

Keywords

Adaptive resonance theory
Classification
Clustering
Regression
Reinforcement learning
Survey

Access to Document

10.1016/j.neunet.2019.09.012

Cite this

@article{a313071c49d343ae939e3692c5031f2b,

title = "A survey of adaptive resonance theory neural network models for engineering applications",

keywords = "Adaptive resonance theory, Classification, Clustering, Regression, Reinforcement learning, Survey",

author = "\{Brito da Silva\}, \{Leonardo Enzo\} and Islam Elnabarawy and Wunsch, \{Donald C.\}",

note = "Publisher Copyright: {\textcopyright} 2019 Elsevier Ltd",

year = "2019",

month = dec,

doi = "10.1016/j.neunet.2019.09.012",

language = "English",

volume = "120",

pages = "167--203",

journal = "Neural Networks",

issn = "0893-6080",

}

TY - JOUR

T1 - A survey of adaptive resonance theory neural network models for engineering applications

AU - Brito da Silva, Leonardo Enzo

AU - Elnabarawy, Islam

AU - Wunsch, Donald C.

PY - 2019/12

Y1 - 2019/12

KW - Adaptive resonance theory

KW - Classification

KW - Clustering

KW - Regression

KW - Reinforcement learning

KW - Survey

UR - https://www.scopus.com/pages/publications/85068457968

UR - https://www.scopus.com/pages/publications/85068457968#tab=citedBy

U2 - 10.1016/j.neunet.2019.09.012

DO - 10.1016/j.neunet.2019.09.012

M3 - Article

C2 - 31610899

SN - 0893-6080

VL - 120

SP - 167

EP - 203

JO - Neural Networks

JF - Neural Networks

ER -

A survey of adaptive resonance theory neural network models for engineering applications

ASJC Scopus Subject Areas

Keywords

Access to Document

Other files and links

Fingerprint

Cite this