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Erschienen in: Soft Computing 17/2019

07.01.2019 | Foundations

Approximation via a double-matroid structure

verfasst von: Xiaonan Li, Huangjian Yi, Zhaohao Wang

Erschienen in: Soft Computing | Ausgabe 17/2019

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Abstract

Approximation is an important issue in rough set theory. In this study, we consider approximation by the matroidal approach. First, we study three lattices induced by an information system. Two of the three lattices are selected as the macrostructure and microstructure for approximation, respectively. Second, based on the two lattices, we define double-matroid lattices, where the upper and lower approximations with respect to an information system are depicted. Since the two lattices are geometric, we actually present approximation by the matroidal approach. Finally, we study the connection between our double-matroid lattices and granular partition lattices. Specifically, the comparison of these two structures is presented in both micro-level and macro-level.

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Fußnoten
1
For ease in working, we denote the partition \(\{1,2\},\{3,4\}\) by (12)(34), and the partition {1,2},{3},{4} simply by its non-trivial block (12).
 
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Metadaten
Titel
Approximation via a double-matroid structure
verfasst von
Xiaonan Li
Huangjian Yi
Zhaohao Wang
Publikationsdatum
07.01.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 17/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-03749-8

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