Decision-oriented rough set methods. (English) Zbl 1444.68228
Yao, Yiyu (ed.) et al., Rough sets, fuzzy sets, data mining, and granular computing. 15th international conference, RSFDGrC 2015, Tianjin, China, November 20–23, 2015. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 9437, 3-12 (2015).
Summary: Rough set theory is a very effective multi-attribute decision analysis tool. The paper reviews four decision-oriented rough set models and methods: dominance-based rough set, three-way decisions, multigranulation decision-theoretic rough set and rough set based multi-attribute group decision-making model. We also introduce some of our group’s works under these four models. Several future research directions of decision-oriented rough sets are presented in the end of the paper.
For the entire collection see [Zbl 1407.68046].
For the entire collection see [Zbl 1407.68046].
MSC:
| 68T37 | Reasoning under uncertainty in the context of artificial intelligence |
References:
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