On the monotonicity of fuzzy inference models

Monotonicity property is very important in real systems. The monotonicity may need to be satisfied in a variety of application domains, e.g., control, medical diagnosis, educational evaluation, etc. A search in the literature reveals that the importance of the monotonicity in fuzzy inference system...

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Main Authors: Seki, H., Tay, K.M
Format: E-Article
Published: Journal of Advanced Computational Intelligence and Intelligent Informatics 2012
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Online Access:http://ir.unimas.my/id/eprint/3041/
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Institution: Universiti Malaysia Sarawak
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spelling my.unimas.ir.30412015-03-24T00:56:45Z http://ir.unimas.my/id/eprint/3041/ On the monotonicity of fuzzy inference models Seki, H. Tay, K.M TK Electrical engineering. Electronics Nuclear engineering Monotonicity property is very important in real systems. The monotonicity may need to be satisfied in a variety of application domains, e.g., control, medical diagnosis, educational evaluation, etc. A search in the literature reveals that the importance of the monotonicity in fuzzy inference system has been highlighted. Therefore, this paper surveys the works relating the monotonicity for various fuzzy inference systems. It firstly focuses on the monotonicity of the Mamdani inference model. Themonotonicity ofMamdani model is shown by using a defuzzification method in cases of three t-norms. Secondly, the monotonicity conditions and applications of the T–S inference model are stated. Finally, the monotonicity of the single input type fuzzy inference models is surveyed. Journal of Advanced Computational Intelligence and Intelligent Informatics 2012 E-Article NonPeerReviewed Seki, H. and Tay, K.M (2012) On the monotonicity of fuzzy inference models. Journal of Advanced Computational Intelligence and Intelligent Informatics, 16 (5). pp. 592-602. http://www.fujipress.jp/finder/xslt.php?mode=present&inputfile=JACII001600050005.xml
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Seki, H.
Tay, K.M
On the monotonicity of fuzzy inference models
description Monotonicity property is very important in real systems. The monotonicity may need to be satisfied in a variety of application domains, e.g., control, medical diagnosis, educational evaluation, etc. A search in the literature reveals that the importance of the monotonicity in fuzzy inference system has been highlighted. Therefore, this paper surveys the works relating the monotonicity for various fuzzy inference systems. It firstly focuses on the monotonicity of the Mamdani inference model. Themonotonicity ofMamdani model is shown by using a defuzzification method in cases of three t-norms. Secondly, the monotonicity conditions and applications of the T–S inference model are stated. Finally, the monotonicity of the single input type fuzzy inference models is surveyed.
format E-Article
author Seki, H.
Tay, K.M
author_facet Seki, H.
Tay, K.M
author_sort Seki, H.
title On the monotonicity of fuzzy inference models
title_short On the monotonicity of fuzzy inference models
title_full On the monotonicity of fuzzy inference models
title_fullStr On the monotonicity of fuzzy inference models
title_full_unstemmed On the monotonicity of fuzzy inference models
title_sort on the monotonicity of fuzzy inference models
publisher Journal of Advanced Computational Intelligence and Intelligent Informatics
publishDate 2012
url http://ir.unimas.my/id/eprint/3041/
http://www.fujipress.jp/finder/xslt.php?mode=present&inputfile=JACII001600050005.xml
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