Premium
Intuitionistic fuzzy rough sets: at the crossroads of imperfect knowledge
Author(s) -
Cornelis Chris,
De Cock Martine,
Kerre Etienne E.
Publication year - 2003
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/1468-0394.00250
Subject(s) - rough set , vagueness , computer science , fuzzy set , generalization , dominance based rough set approach , extension (predicate logic) , type 2 fuzzy sets and systems , artificial intelligence , imperfect , fuzzy logic , data mining , fuzzy set operations , theoretical computer science , mathematics , mathematical analysis , linguistics , philosophy , programming language
Just like rough set theory, fuzzy set theory addresses the topic of dealing with imperfect knowledge. Recent investigations have shown how both theories can be combined into a more flexible, more expressive framework for modelling and processing incomplete information in information systems. At the same time, intuitionistic fuzzy sets have been proposed as an attractive extension of fuzzy sets, enriching the latter with extra features to represent uncertainty (on top of vagueness). Unfortunately, the various tentative definitions of the concept of an ‘intuitionistic fuzzy rough set’ that were raised in their wake are a far cry from the original objectives of rough set theory. We intend to fill an obvious gap by introducing a new definition of intuitionistic fuzzy rough sets, as the most natural generalization of Pawlak's original concept of rough sets.