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:	Article
Published:	Journal of Advanced Computational Intelligence and Intelligent Informatics 2012
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://ir.unimas.my/3041/ http://ir.unimas.my/3041/

id	unimas-3041
recordtype	eprints
spelling	unimas-30412015-03-24T00:56:45Z http://ir.unimas.my/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 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
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Sarawak
building	UNIMAS Institutional Repository
collection	Online Access
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	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/3041/ http://ir.unimas.my/3041/
first_indexed	2018-09-06T14:55:23Z
last_indexed	2018-09-06T14:55:23Z
_version_	1610870395961868288

On the monotonicity of fuzzy inference models

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