Multi knowledge based rough approximations and applications

► We used a special neighborhood to define lower and upper approximations of any set. ► Generalized these definitions in two different ways. ► The first way is based on the intersection of all these neighborhoods. ► The second generalized based on the intersection and union of approximations. ► We i...

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Bibliographic Details
Published in:Knowledge-based systems 2012-02, Vol.26, p.20-29
Main Author: Abu-Donia, H.M.
Format: Article
Language:English
Subjects:
Accuracy
Accuracy measure
Knowledge discovery
Left neighborhoods
Lower and upper approximations
Right neighborhoods
Rough set theory
Rough sets
Topological spaces
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Summary:► We used a special neighborhood to define lower and upper approximations of any set. ► Generalized these definitions in two different ways. ► The first way is based on the intersection of all these neighborhoods. ► The second generalized based on the intersection and union of approximations. ► We introduced new general definitions for some Pawlak’s definitions. Rough set theory is an important technique in knowledge discovery in databases. In covering based rough sets, many types of rough set models are established in recent years. This paper presents new types of rough set approximations using multi knowledge base, that is, family of finite number of (reflexive, tolerance, dominance, equivalence) relations by two ways. Properties and applications of these approximation operators are studied and many examples are given.
ISSN:0950-7051
1872-7409
DOI:10.1016/j.knosys.2011.06.010