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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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Fuzzy entropy and conditioning
Information Sciences, 1986A new nonprobabilistic entropy measure is introduced in the context of fuzzy sets or messages. Fuzzy units, or fits, replace bits in a new framework of fuzzy information theory. An appropriate measure of entropy or fuzziness of messages is shown to be a simple ratio of distances: the distances between the fuzzy message and its nearest and farthest ...
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On fuzzy entropy and topological entropy of fuzzy extensions of dynamical systems
Fuzzy Sets and Systems, 2017The concept of degrees of fuzziness due to \textit{A. De Luca} and \textit{S. Termini} [Inf. Control 20, 301--312 (1972; Zbl 0239.94028)] and fuzzy topological entropies and their relationships are studied. Such concepts are necessary for a proper understanding of fuzzy systems generated from crisp discrete dynamical systems.
Jose S. Cánovas, Jiří Kupka
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Relative entropy collaborative fuzzy clustering method
Pattern Recognition, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Türkşen, İsmail Burhan +2 more
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Rough–Fuzzy Entropy in Neighbourhood Characterization
2019The Entropy has been used to characterize the neighbourhood of a sample on the base of its k Nearest Neighbour when data are imbalanced and many measures of Entropy have been proposed in the literature to better cope with vagueness, exploiting fuzzy logic, rough set theory and their derivatives.
Maratea A., Ferone A.
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Fuzzy clustering and fuzzy entropy based classification model
2010 6th International Conference on Emerging Technologies (ICET), 2010In Pattern recognition, ensembles of classifiers are used to increase the performance and accuracy of classification systems. The creation of ensembles, selection of base classifiers and combining the decisions of the classifiers is an active research area.
Muhammad A. Khan +3 more
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Fuzzy σ-algebras and conditional entropy
Fuzzy Sets and Systems, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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ON THE ENTROPY OF FUZZY EVENTS
Kybernetes, 1983Entropy measures of fuzzy events of a set X with a (not necessary finite) positive measure µ defined on a σ‐algebra of subsets of X are studied. Using fuzzy measures and fuzzy integrals, a theorem is presented, which gives a sufficient condition for the existence of entropy measures under a list of reasonable axioms.
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A New Fuzzy Entropy for Intuitionistic Fuzzy Sets
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007Fuzzy entropy is an important concept of intuitionistic fuzzy sets (IFSs). In this paper, the resources of the entropy of an intuitionistic fuzzy set are analyzed. It is pointed out that the fuzzy entropy of an IFS comes from uncertainty and unknown information.
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