Results 281 to 290 of about 702,978 (335)
An analytical optimal calibration framework of bonded particle model for rock strength envelop modelling. [PDF]
Sci RepZhou X, Xu H, Gong Q, Ma Y, Xie W.
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A novel algorithmic multi-attribute decision-making framework for the evaluation of energy systems using rough approximations of hypersoft sets. [PDF]
HeliyonAbdullah M +3 more
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Reply to: Not just the alveolar trill, but all "r-like" sounds are associated with roughness across languages, pointing to a more general link between sound and touch. [PDF]
Sci RepSóskuthy M +3 more
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Research on early warning model of coal spontaneous combustion based on interpretability. [PDF]
Sci RepZhao H +5 more
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The Association Between Sexual Victimization History and Consensual and Nonconsensual Rough Sex: Findings from a U.S. Nationally Representative Survey. [PDF]
Psychol ViolencePeterson ZD +4 more
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ROUGH FUZZY SETS AND FUZZY ROUGH SETS*
International Journal of General Systems, 1990The notion of a rough set introduced by Pawlak has often been compared to that of a fuzzy set, sometimes with a view to prove that one is more general, or, more useful than the other. In this paper we argue that both notions aim to different purposes.
Dubois, Didier, Prade, Henri
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Communications of the ACM, 1995
Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge ...
Pawlak, Zdzisław +3 more
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Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge ...
Pawlak, Zdzisław +3 more
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Fuzzy Sets and Systems, 1992
The authors introduce the concept of a fuzzy rough set by fuzzifying rough sets. They show some easy properties of fuzzy rough sets.
Saptarshi Majumdar, S. Nanda
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The authors introduce the concept of a fuzzy rough set by fuzzifying rough sets. They show some easy properties of fuzzy rough sets.
Saptarshi Majumdar, S. Nanda
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Chemometrics and Intelligent Laboratory Systems, 1999 Abstract The basic concepts of the rough set theory are introduced and adequately illustrated. An example of the rough set theory application to the QSAR classification problem is presented. Numerous earlier applications of rough set theory to the various scientific domains suggest that it also can be a useful tool for the analysis of inexact ...
Walczak, Beata, Massart, Desire
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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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