Attribute Reduction in Stochastic Information Systems Based on α-Dominance
Yıl 2017,
Cilt: 10 Sayı: 2, 211 - 219, 28.04.2017
Emel Kızılkaya Aydoğan
,
Mihrimah Özmen
Öz
Rough set has been commonly taken part in literature
to examine inadequate and incomplete
information systems. The efficiency of rough set with stochastic data observed
for developing convenience and scalability. In this study, we use a ranking
approach for attribute reduction in stochastic information systems and
generalized this via presenting a dominance relation. We obtained the rough set approach of
attribute reduction in stochastic information systems by establishing the
dominance degrees. Furthermore, attribute reduction methods are studied by
considering discernibility matrix and this approach is applied to explanatory
examples to demonstrate its validity. Also this research proposes many research
fields and new application areas show a tendency to concerning rough set
approach to stochastic information systems.
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