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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Journal of Advanced Computational Intelligence and Intelligent Informatics
2012
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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 |
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TK Electrical engineering. Electronics Nuclear engineering Seki, H. Tay, K.M On the monotonicity of fuzzy inference models |
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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. |
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E-Article |
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Seki, H. Tay, K.M |
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Seki, H. Tay, K.M |
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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 |
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Journal of Advanced Computational Intelligence and Intelligent Informatics |
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2012 |
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http://ir.unimas.my/id/eprint/3041/ http://www.fujipress.jp/finder/xslt.php?mode=present&inputfile=JACII001600050005.xml |
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1644509248329089024 |