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International Journal of Approximate Reasoning
Article
License: Elsevier Non-Commercial
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International Journal of Approximate Reasoning
Article . 2008
License: Elsevier Non-Commercial
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International Journal of Approximate Reasoning
Article . 2008 . Peer-reviewed
License: Elsevier Non-Commercial
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Axiomatic systems for rough sets and fuzzy rough sets

Authors: Guilong Liu;

Axiomatic systems for rough sets and fuzzy rough sets

Abstract

AbstractRough set theory is an important tool for approximate reasoning about data. Axiomatic systems of rough sets are significant for using rough set theory in logical reasoning systems. In this paper, outer product method are used in rough set study for the first time. By this approach, we propose a unified lower approximation axiomatic system for Pawlak’s rough sets and fuzzy rough sets. As the dual of axiomatic systems for lower approximation, a unified upper approximation axiomatic characterization of rough sets and fuzzy rough sets without any restriction on the cardinality of universe is also given. These rough set axiomatic systems will help to understand the structural feature of various approximate operators.

Related Organizations
Keywords

Fuzzy sets, Upper approximations, Axioms, Artificial Intelligence, Applied Mathematics, Lower approximations, Fuzzy rough sets, Rough sets, Software, Theoretical Computer Science

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    89
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
89
Top 10%
Top 10%
Top 10%
hybrid