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Erschienen in: International Journal of Machine Learning and Cybernetics 3/2017

11.12.2015 | Original Article

General relation-based variable precision rough fuzzy set

verfasst von: Eric C. C. Tsang, Bingzhen Sun, Weimin Ma

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 3/2017

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Abstract

In order to effectively handle the real-valued data sets in practice, it is valuable from theoretical and practical aspects to combine fuzzy rough set and variable precision rough set so that a powerful tool can be developed. That is, the model of fuzzy variable precision rough set, which not only can handle numerical data but also is less sensitive to misclassification and perturbation,In this paper, we propose a new variable precision rough fuzzy set by introducing the variable precision parameter to generalized rough fuzzy set, i.e., the variable precision rough fuzzy set based on general relation. We, respectively, define the variable precision rough lower and upper approximations of any fuzzy set and it level set with variable precision parameter by constructive approach. Also, we present the properties of the proposed model in detail. Meanwhile, we establish the relationship between the variable precision rough approximation of a fuzzy set and the rough approximation of the level set for a fuzzy set. Furthermore, we give a new approach to uncertainty measure for variable precision rough fuzzy set established in this paper in order to overcome the limitations of the traditional methods. Finally, some numerical example are used to illuminate the validity of the conclusions given in this paper.

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Metadaten
Titel
General relation-based variable precision rough fuzzy set
verfasst von
Eric C. C. Tsang
Bingzhen Sun
Weimin Ma
Publikationsdatum
11.12.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 3/2017
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-015-0465-z

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