Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6004
Title: A new intuitionistic fuzzy rough set approach for decision support
Authors: Chai, J
Liu, JNK
Li, A
Keywords: Multicriteria decision analysis
Rough set
Intuitionistic fuzzy set
Rule-based approach
Sorting
Issue Date: Aug-2012
Publisher: Springer Berlin Heidelberg
Source: In T. Rui Li, H. S. Nguyen, G. Wang, J. W. Grzymala-Busse, R. Janicki, A. E. Hassanien & H. Yu (eds.), Rough sets and knowledge technology: 7th International Conference, RSKT 2012, Chengdu, China, August 17-20, 2012 : proceedings, pp. 71-80 How to cite?
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.
URI: http://hdl.handle.net/10397/6004
ISBN: 978-3-642-31899-3 (print)
978-3-642-31900-6 (online)
DOI: 10.1007/978-3-642-31900-6_10
Rights: © Springer-Verlag Berlin Heidelberg 2012
"Chai, J., Liu, J. N. K. & Li, A. (2012). A New Intuitionistic Fuzzy Rough Set Approach for Decision Support. In T. Rui Li, H. S. Nguyen, G. Wang, J. W. Grzymala-Busse, R. Janicki, A. E. Hassanien & H. Yu (eds.), Rough sets and knowledge technology: 7th International Conference, RSKT 2012, Chengdu, China, August 17-20, 2012 (pp. 71-80). Berlin; New York: Springer." is available online at http://dx.doi.org/10.1007/978-3-642-31900-6_10. The final publication is available at link.springer.com.
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