A new intuitionistic fuzzy rough set approach for decision support

Authors:
Junyi Chai;James N. K. Liu;Anming Li
Affiliations:
Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR;Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR;Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
Venue:
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
Year:
2012

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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.