Results 171 to 180 of about 185,811 (251)
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Fuzzy Sets and Systems, 2000
In the paper the authors define a measure of fuzziness in a rough set and investigate its properties. Every approximation space \((U, R)\), where \(R\) is an equivalence relation on \(U\), and a subset \(X\) of \(U\) determine a rough set \(R(X)\). Let \(\operatorname {card}(Y)\) denote the cardinality of \(Y\). With \((U, R)\) and \(X\) we associate a
Kankana Chakrabarty +2 more
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In the paper the authors define a measure of fuzziness in a rough set and investigate its properties. Every approximation space \((U, R)\), where \(R\) is an equivalence relation on \(U\), and a subset \(X\) of \(U\) determine a rough set \(R(X)\). Let \(\operatorname {card}(Y)\) denote the cardinality of \(Y\). With \((U, R)\) and \(X\) we associate a
Kankana Chakrabarty +2 more
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Active Incremental Feature Selection Using a Fuzzy-Rough-Set-Based Information Entropy
IEEE transactions on fuzzy systems, 2020Feature selection is a popular technique of preprocessing data. In order to deal with dynamic or large data, incremental feature selection has been developed, in which the features selected from existing data are integrated with those mined from both ...
Xiao Zhang +4 more
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Novel fuzzy rough set models and corresponding applications to multi-criteria decision-making
Fuzzy Sets Syst., 2020By means of a fuzzy coimplication operator J and a triangular conorm S , we set forth two pairs of ( J , S ) -fuzzy rough set models, which are generalizations of fuzzy rough sets.
Kai Zhang, J. Zhan, Weizhi Wu
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The Fuzziness Measure in Fuzzy Rough Sets
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008The paper studies the fuzziness measure in fuzzy rough sets. By making use of the support set of fuzzy sets, a rough membership function for fuzzy sets based on fuzzy relation is introduced. Simultaneously, a fuzziness measure of fuzzy rough sets from total mean fuzzy degree is proposed.
Yue-Jin Lv +2 more
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TOPSIS-WAA method based on a covering-based fuzzy rough set: An application to rating problem
Information Sciences, 2020In this paper, we firstly study two pairs of covering-based fuzzy rough set models and propose the TOPSIS-WAA method based on a covering-based fuzzy rough set.
Kai Zhang, J. Zhan, Xizhao Wang
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International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2020
In this paper, we provide a definition of α-fuzzified lower and upper approximations for fuzzy sets based on the α-cut of fuzzy binary relations. We show that the definition is a proper generalization of the previous one for approximations of crisp sets and compare it with an existing definition in the context of fuzzy tolerance relation.
Yu-Ru Syau, En-Bing Lin, Churn-Jung Liau
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In this paper, we provide a definition of α-fuzzified lower and upper approximations for fuzzy sets based on the α-cut of fuzzy binary relations. We show that the definition is a proper generalization of the previous one for approximations of crisp sets and compare it with an existing definition in the context of fuzzy tolerance relation.
Yu-Ru Syau, En-Bing Lin, Churn-Jung Liau
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Information Sciences, 2019
By means of a fuzzy logical implicator and a t-norm (respectively denoted I and T ), we introduce covering based multigranulation ( I , T ) -fuzzy rough set models from fuzzy β-neighborhoods.
J. Zhan, B. Sun, J. Alcantud
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By means of a fuzzy logical implicator and a t-norm (respectively denoted I and T ), we introduce covering based multigranulation ( I , T ) -fuzzy rough set models from fuzzy β-neighborhoods.
J. Zhan, B. Sun, J. Alcantud
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Fuzzy rough set-based attribute reduction using distance measures
Knowledge-Based Systems, 2019Attribute reduction is one of the most important applications of fuzzy rough sets in machine learning and pattern recognition. Most existing methods employ the intersection operation of fuzzy relations to construct the dependency function of attribute ...
Changzhong Wang +3 more
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Probabilistic Rough Sets Characterized by Fuzzy Sets
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2004Theories of fuzzy sets and rough sets have emerged as two major mathematical approaches for managing uncertainty that arises from inexact, noisy, or incomplete information. They are generalizations of classical set theory for modelling vagueness and uncertainty.
Li-Li Wei, Wen-Xiu Zhang
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Computers & industrial engineering, 2020
For a considered multiple attribute group decision making (MAGDM) problem, there may be different evaluation attribute set used by different decision-makers for the same decision making problem.
B. Sun +5 more
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For a considered multiple attribute group decision making (MAGDM) problem, there may be different evaluation attribute set used by different decision-makers for the same decision making problem.
B. Sun +5 more
semanticscholar +1 more source