Subsethood measures, also known as set-inclusion measures, inclusion degrees, rough
inclusions, and rough-inclusion functions, are generalizations of the set-inclusion relation for …

The notion of rough sets was originally proposed by Pawlak. In Pawlak's rough set theory,
the equivalence relation or partition plays an important role. However, the equivalence …

Rough set data analysis is one of the main application techniques arising from rough set
theory. In this paper we introduce a concept of inclusion degree into rough set theory and …

Pawlak's rough membership functions not only give numerical characterizations of Pawlak's
rough set approximations, but also establishes the relationships between Pawlak's rough …

Distance provides a comprehensible perspective for characterizing the difference between
two objects in a metric space. There are many measures which have been proposed and …

Rough sets: Some extensions - ScienceDirect Skip to main contentSkip to article Elsevier logo
Journals & Books Search RegisterSign in View PDF Download full issue Search ScienceDirect …

Different rough set models may be numerically characterized with evidence theory by
adopting different methodologies. That is to say, the evidence theory-based characteristics …

Rough set theory is a non-statistical approach to handle uncertainty and uncertain
knowledge. It is characterized by two methods called classification (lower and upper …

This paper presents a framework for a systematic study of the rough set theory. Various
views and interpretations of the theory and different approaches to study the theory are …

A generalization of the original idea of rough sets and variable precision rough sets is
introduced. This generalization is based on the concept of absolute and relative rough …