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Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem

Over the last years, the pattern classification is considered one of the most significant domains in artificial intelligence (AI), because it shapes a fundamental in many diverse real live applications where the artificial neural networks (ANNs) and fuzzy logic (FL) are most extensively utilized in...

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Main Authors: Al Sayaydeh, Osama Nayel, Shamaileh, Abeer
Format: Article
Language:English
Published: IJITLS, UAE 2018
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/23976/1/Fuzzy%20Min%20Max%20Neural%20Network%20for%20pattern.pdf
http://umpir.ump.edu.my/id/eprint/23976/
http://journals.sfu.ca/ijitls/index.php/ijitls/article/view/54
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spelling my.ump.umpir.239762019-01-28T01:01:06Z http://umpir.ump.edu.my/id/eprint/23976/ Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem Al Sayaydeh, Osama Nayel Shamaileh, Abeer QA Mathematics Over the last years, the pattern classification is considered one of the most significant domains in artificial intelligence (AI), because it shapes a fundamental in many diverse real live applications where the artificial neural networks (ANNs) and fuzzy logic (FL) are most extensively utilized in pattern classification. In order to construct an effective and robust classifier, researchers have invented hybrid systems that combine both FL and ANNs. The Fuzzy Min Max (FMM) neural network has been proven to be a robust classifier for handling pattern classification issues. Although FMM has several features, it suffers from several limitations. Thus, researchers have introduced a lot of improvements to beat the shortcomings of FMM neural network. This paper focuses on a complete review of developments carried out on FMM neural network for addressing the complexity problem in order to help new researchers in identifying the recent strategies used to address the complexity problem. IJITLS, UAE 2018 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23976/1/Fuzzy%20Min%20Max%20Neural%20Network%20for%20pattern.pdf Al Sayaydeh, Osama Nayel and Shamaileh, Abeer (2018) Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem. International Journal of Information Technology and Language Studies (IJITLS), 2 (3). pp. 110-117. ISSN 2521-8727 http://journals.sfu.ca/ijitls/index.php/ijitls/article/view/54
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Al Sayaydeh, Osama Nayel
Shamaileh, Abeer
Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem
description Over the last years, the pattern classification is considered one of the most significant domains in artificial intelligence (AI), because it shapes a fundamental in many diverse real live applications where the artificial neural networks (ANNs) and fuzzy logic (FL) are most extensively utilized in pattern classification. In order to construct an effective and robust classifier, researchers have invented hybrid systems that combine both FL and ANNs. The Fuzzy Min Max (FMM) neural network has been proven to be a robust classifier for handling pattern classification issues. Although FMM has several features, it suffers from several limitations. Thus, researchers have introduced a lot of improvements to beat the shortcomings of FMM neural network. This paper focuses on a complete review of developments carried out on FMM neural network for addressing the complexity problem in order to help new researchers in identifying the recent strategies used to address the complexity problem.
format Article
author Al Sayaydeh, Osama Nayel
Shamaileh, Abeer
author_facet Al Sayaydeh, Osama Nayel
Shamaileh, Abeer
author_sort Al Sayaydeh, Osama Nayel
title Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem
title_short Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem
title_full Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem
title_fullStr Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem
title_full_unstemmed Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem
title_sort fuzzy min max neural network for pattern classification: an overview of complexity problem
publisher IJITLS, UAE
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/23976/1/Fuzzy%20Min%20Max%20Neural%20Network%20for%20pattern.pdf
http://umpir.ump.edu.my/id/eprint/23976/
http://journals.sfu.ca/ijitls/index.php/ijitls/article/view/54
_version_ 1643669732898897920
score 13.211869

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