Journal
INFORMATION SCIENCES
Volume 221, Issue -, Pages 215-229Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2012.09.010
Keywords
Interval-valued intuitionistic fuzzy set; Information systems; Dominance relation; Rough set model; Reduction; Rule extraction
Categories
Funding
- Natural Science Foundation of China [61170105]
- Jiangsu Natural Science Foundation of China [BK2009395]
- Priority Academic Program Development of Jiangsu Higher Education Institutions (Audition Science and Technology)
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Interval-valued intuitionistic fuzzy information systems are generalizations of conventional fuzzy-valued information systems. We introduce a dominance relation in the framework of interval-valued intuitionistic fuzzy information systems to come up with the concept we call a dominance-based interval-valued intuitionistic fuzzy information system (DIIFIS). This system is used to establish a dominance-based rough set model, which is grounded primarily on the substitution of the indiscernibility relation in the classic rough set theory with the aforementioned dominance-based relation. This relation is defined by the score and accuracy of interval-valued intuitionistic fuzzy value. To simplify knowledge representation and extract useful and simple dominance-based interval-valued intuitionistic fuzzy rules, we present two attribute reduction approaches to eliminating redundant information. To demonstrate the potential of these approaches, we apply them to computer auditing risk assessment, decision-making problems in wealth management, and pattern classification. Our findings confirm that the proposed rough set model is an effective means of extracting knowledge from dominance-based interval-valued intuitionistic fuzzy information systems. (C) 2012 Elsevier Inc. All rights reserved.
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