Paper Info
Title
A new intuitionistic fuzzy rough set approach for decision support
Abstract
The rough set theory was proved of its effectiveness in dealing with the imprecise and ambiguous information. Dominance-based Rough Set Approach (DRSA), as one of the extensions, is effective and fundamentally important for Multiple Criteria Decision Analysis (MCDA). However, most of existing DRSA models cannot directly examine uncertain information within rough boundary regions, which might miss the significant knowledge for decision support. In this paper, we propose a new believe factor in terms of an intuitionistic fuzzy value as foundation, further to induce a kind of new uncertain rule, called believable rules, for better performance in decision-making. We provide an example to demonstrate the effectiveness of the proposed approach in multicriteria sorting and also a comparison with existing representative DRSA models.
Year
DOI
Venue
2012
10.1007/978-3-642-31900-6_10
RSKT
Keywords
Field
DocType
rough boundary region,decision support,representative drsa model,rough set theory,believable rule,new uncertain rule,drsa model,dominance-based rough set approach,uncertain information,ambiguous information,multiple criteria decision analysis,intuitionistic fuzzy rough set,sorting,rough set
Multiple-criteria decision analysis,Computer science,Fuzzy logic,Decision support system,Sorting,Rough set,Fuzzy rough sets,Artificial intelligence,Dominance-based rough set approach,Machine learning
Conference
Citations 
PageRank 
References 
3
0.43
11
Authors
3
Name
Order
Citations
PageRank
Junyi Chai121312.09
James N. K. Liu252944.35
Anming Li351.47