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The notion of roughness of a fuzzy set
Fuzzy Sets and Systems, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Inés Couso +2 more
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Journal of Intelligent & Fuzzy Systems, 2019
In this manuscript we develop a comprehensive model to tackle decision making problems where strong points of view are in the favor and against some projects, entities or plans.
A. Hussain, M. Ali, T. Mahmood
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In this manuscript we develop a comprehensive model to tackle decision making problems where strong points of view are in the favor and against some projects, entities or plans.
A. Hussain, M. Ali, T. Mahmood
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2006
A rough fuzzy set is a pair of fuzzy sets resulting from the approximation of a fuzzy set in a crisp approximation space. A rough fuzzy set algebra is a fuzzy set algebra with added dual pair of rough fuzzy approximation operators. In this paper, structures of rough fuzzy set algebras are studied. It is proved that if a system $({\cal F}(U), \cap, \cup,
Wei-Zhi Wu 0001, You-Hong Xu
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A rough fuzzy set is a pair of fuzzy sets resulting from the approximation of a fuzzy set in a crisp approximation space. A rough fuzzy set algebra is a fuzzy set algebra with added dual pair of rough fuzzy approximation operators. In this paper, structures of rough fuzzy set algebras are studied. It is proved that if a system $({\cal F}(U), \cap, \cup,
Wei-Zhi Wu 0001, You-Hong Xu
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Axiomatics for fuzzy rough sets
Fuzzy Sets and Systems, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nehad N. Morsi, Mohammed Mostafa Yakout
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An extension of rough fuzzy set
Journal of Intelligent & Fuzzy Systems, 2016In rough fuzzy set, equivalence relation is used for approximating the target concept, which is a fuzzy set. In this paper, we extend the equivalence relation in rough fuzzy set to tolerance relation, and propose an extended model named tolerance rough fuzzy set.
Junhai Zhai, Sufang Zhang, Yao Zhang
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Attribute reduction for multi-label learning with fuzzy rough set
Knowledge-Based Systems, 2018In multi-label learning, each sample is related to multiple labels simultaneously, and attribute space of samples is with high-dimensionality. Therefore, the key issue for attribute reduction in multi-label data is to measure the quality of each ...
Yaojin Lin +3 more
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Where Rough Sets and Fuzzy Sets Meet
Fundamenta Informaticae, 2015The title of this note announces an attempt at pointing to particular points where rough set and fuzzy set approaches to decision making are close to each other, the closeness meaning that formal approaches to behaviour of the two at those points can be given in an analogous form. This by no means implies that the two can be unified as theories dealing
Lech Polkowski, Maria Semeniuk-Polkowska
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2004
In this paper we introduce a new class of algebras, called extended residuated lattices. Basing on this structure we present an algebraic generalization of approximation operators and rough sets determined by abstract counterparts of fuzzy logical operations.
Anna Maria Radzikowska, Etienne E. Kerre
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In this paper we introduce a new class of algebras, called extended residuated lattices. Basing on this structure we present an algebraic generalization of approximation operators and rough sets determined by abstract counterparts of fuzzy logical operations.
Anna Maria Radzikowska, Etienne E. Kerre
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Rough Soft Sets in Fuzzy Setting
2013Fuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing with uncertainties and are closely related. In the paper, we define the notion of a soft set in L-set theory, introduce several operators for L-soft set theory, and investigate the rough operators on the set of all L-soft sets induced by the rough operators on L X
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A fuzzy rough set-based feature selection method using representative instances
Knowledge-Based Systems, 2018The fuzzy rough set theory has been widely used to deal with uncertainty in real-valued or even complex data, in which one of the most concerned issues is feature selection.
Xiao Zhang +3 more
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