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The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression

In this study, we develop a comprehensive design process of granular fuzzy rule-based systems. These constructs arise as a result of a structural compression of fuzzy rule-based systems in which a subset of originally existing rules is retained. Because of the reduced subset of the originally exist...

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Main Authors: Sharifah Sakinah, Syed Ahmad, Pedrycz, Witold
Format: Article
Language:English
Published: Springer International Publishing 2016
Subjects:
T Technology (General)
Online Access:http://eprints.utem.edu.my/id/eprint/17282/3/The%20Development%20Of%20Granular%20Rule-Based%20Systems%3B%20A%20Study%20In%20Structural%20Model%20Compression.pdf
http://eprints.utem.edu.my/id/eprint/17282/
http://download.springer.com/static/pdf/306/art%253A10.1007%252Fs41066-016-0022-5.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs41066-016-0022-5&token2=exp=1475220437~acl=%2Fstatic%2Fpdf%2F306%2Fart%25253A10.1007%25252Fs41066-016-002
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spelling my.utem.eprints.172822021-09-12T23:38:55Z http://eprints.utem.edu.my/id/eprint/17282/ The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression Sharifah Sakinah, Syed Ahmad Pedrycz, Witold T Technology (General) In this study, we develop a comprehensive design process of granular fuzzy rule-based systems. These constructs arise as a result of a structural compression of fuzzy rule-based systems in which a subset of originally existing rules is retained. Because of the reduced subset of the originally existing rules, the remaining rules are made more abstract (general) by expressing their conditions in the form of granular fuzzy sets (such as interval-valued fuzzy sets, rough fuzzy sets, probabilistic fuzzy sets, etc.), hence the name of granular fuzzy rule-based systems emerging during the compression of the rule bases. The design of these systems dwells upon an important mechanism of allocation of information granularity using which the granular fuzzy rules are formed. The underlying optimization consists of two phases: structural (being of combinatorial character in which a subset of rules is selected) and parametric (when the conditions of the selected rules are made granular through an optimal allocation of information granularity). We implement the cooperative particle swarm optimization to solve optimization problem. A number of experimental studies are reported; those include fuzzy rule-based systems. Springer International Publishing 2016 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/17282/3/The%20Development%20Of%20Granular%20Rule-Based%20Systems%3B%20A%20Study%20In%20Structural%20Model%20Compression.pdf Sharifah Sakinah, Syed Ahmad and Pedrycz, Witold (2016) The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression. Granular Computing. pp. 1-12. ISSN 2364-4966 http://download.springer.com/static/pdf/306/art%253A10.1007%252Fs41066-016-0022-5.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs41066-016-0022-5&token2=exp=1475220437~acl=%2Fstatic%2Fpdf%2F306%2Fart%25253A10.1007%25252Fs41066-016-002 10.1007/s41066-016-0022-5
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Sharifah Sakinah, Syed Ahmad
Pedrycz, Witold
The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression
description In this study, we develop a comprehensive design process of granular fuzzy rule-based systems. These constructs arise as a result of a structural compression of fuzzy rule-based systems in which a subset of originally existing rules is retained. Because of the reduced subset of the originally existing rules, the remaining rules are made more abstract (general) by expressing their conditions in the form of granular fuzzy sets (such as interval-valued fuzzy sets, rough fuzzy sets, probabilistic fuzzy sets, etc.), hence the name of granular fuzzy rule-based systems emerging during the compression of the rule bases. The design of these systems dwells upon an important mechanism of allocation of information granularity using which the granular fuzzy rules are formed. The underlying optimization consists of two phases: structural (being of combinatorial character in which a subset of rules is selected) and parametric (when the conditions of the selected rules are made granular through an optimal allocation of information granularity). We implement the cooperative particle swarm optimization to solve optimization problem. A number of experimental studies are reported; those include fuzzy rule-based systems.
format Article
author Sharifah Sakinah, Syed Ahmad
Pedrycz, Witold
author_facet Sharifah Sakinah, Syed Ahmad
Pedrycz, Witold
author_sort Sharifah Sakinah, Syed Ahmad
title The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression
title_short The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression
title_full The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression
title_fullStr The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression
title_full_unstemmed The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression
title_sort development of granular rule-based systems: a study in structural model compression
publisher Springer International Publishing
publishDate 2016
url http://eprints.utem.edu.my/id/eprint/17282/3/The%20Development%20Of%20Granular%20Rule-Based%20Systems%3B%20A%20Study%20In%20Structural%20Model%20Compression.pdf
http://eprints.utem.edu.my/id/eprint/17282/
http://download.springer.com/static/pdf/306/art%253A10.1007%252Fs41066-016-0022-5.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs41066-016-0022-5&token2=exp=1475220437~acl=%2Fstatic%2Fpdf%2F306%2Fart%25253A10.1007%25252Fs41066-016-002
_version_ 1712288913814454272
score 13.211869

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