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Measures of Observables and Measures of Fuzziness
2012The key aims of modern scientific work have generally been to find relationships between observed phenomena, construct mathematical formulas that describe these relationships, take measurements of the observables, and define axioms using terms that are as exact as possible.
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Inclusion measures, similarity measures, and the fuzziness of fuzzy sets and their relations
International Journal of Intelligent Systems, 2006Summary: The inclusion measure, the similarity measure, and the fuzziness of fuzzy sets are three important measures in fuzzy set theory. In this article, we investigate the relations among inclusion measures, similarity measures, and the fuzziness of fuzzy sets, prove eight theorems that inclusion measures, similarity measures, and the fuzziness of ...
Wenyi Zeng, Hongxing Li 0004
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Measuring the Fuzziness of Sets
Journal of Cybernetics, 1974Set theory begins to be useful when there is some natural criterion for defining belonging to a set. Sets of objects without properties are uninteresting. Elements are assigned to sets because they share properties or conform to a rule. A set of elements is said to be fuzzy when we allow some elements to belong to the set unequally or more strongly ...
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2010
A definition for the entropy of fuzzy measures defined on set systems is proposed. The underlying set is not necessarily the whole power set, but satisfy a condition of regularity. This definition encompasses the classical definition of Shannon for probability measures, as well as the definition of Marichal et al.
Aoi Honda, Michel Grabisch
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A definition for the entropy of fuzzy measures defined on set systems is proposed. The underlying set is not necessarily the whole power set, but satisfy a condition of regularity. This definition encompasses the classical definition of Shannon for probability measures, as well as the definition of Marichal et al.
Aoi Honda, Michel Grabisch
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On the weak convergence of sequences of fuzzy measures and metric of fuzzy measures
Fuzzy Sets and Systems, 2000A fuzzy measure is considered on the \(\sigma\)-algebra \({\mathcal A}\) of Borel subsets of a metric space (i.e., \(\mu:{\mathcal A}\to [0,\infty]\), \(\mu(\emptyset)= 0\), \(\mu\) monotone and continuous from above and from below) together with the Sugeno integral \[ \int_A f d\mu= \bigvee_{\alpha\geq 0} [\alpha\wedge \mu(A\cap \{f\geq \alpha\})]. \]
Guijun Wang, Xiaoping Li
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Fuzzy Sets and Systems, 1998
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Fuzzy Sets and Systems, 1999
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Congxin Wu +3 more
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Congxin Wu +3 more
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On the entropy of fuzzy measures
IEEE Transactions on Fuzzy Systems, 2000Fuzzy measures provides a structure for modeling the knowledge available about variables whose values are unknown and uncertain. A large class of different types of uncertainty can be represented in this framework. In this work, we provide a measure of entropy that can be used to calculate the amount of uncertainty associated with a fuzzy measure.
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Measures of fuzziness of fuzzy events
Fuzzy Sets and Systems, 1987We prove some new results on two families of fuzzy integrals defined in a previous paper, and by means of them we obtain entropy measures of fuzzy sets (not necessarily finite) which contain as particular cases the measures of Batle and Trillas, and Weber.
Suárez García, Fermín +1 more
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Fuzzy measures and coherent join measures
International Journal of Intelligent Systems, 2011In assigning weights and scores in a decision problem usually we assume that they are finitely additive normalized measures, i.e., from the formal point of view, finitely additive probabilities. The normalization requirement sometimes appears as an actual restriction.
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