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Uncertainty and incompleteness of knowledge are widespread phenomena in information systems. Rough set theory is a tool for dealing with granularity and vagueness in data analysis. Rough set method has already been applied to various fields such as process control, economics, medical diagnosis, biochemistry, environmental science, biology, chemistry psychology, and conflict analysis. Covering-based...
Rough set theory has been proposed by Pawlak as a tool for dealing with the vagueness and granularity in information systems. The core concepts of classical rough sets are lower and upper approximations based on equivalence relations, or partitions. This paper studies covering-based generalized rough sets. In this setting, a covering can generate a lower approximation operation and an upper approximation...
Rough set theory and fuzzy set theory are two powerful tools to deal with uncertainty and incompleteness of knowledge in information systems. This paper explores a type of covering-based fuzzy rough set theory based on coverings that combine the above two theories. We present basic concepts and properties of this kind of fuzzy rough sets.
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