Necessity measures and parametric inclusion relations of fuzzy sets
Fundamenta Informaticae
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Possibility and necessity measure specification using modifiers for decision making under fuzziness
Fuzzy Sets and Systems - Special issue: Preference modelling and applications
Rough Set Analysis of Preference-Ordered Data
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Dominance-Based Rough Set Approach to Reasoning About Ordinal Data
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
An Incremental Updating Algorithm for Core Computing in Dominance-Based Rough Set Model
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Rough Set Approach to Knowledge Discovery about Preferences
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Fuzzy preference based rough sets
Information Sciences: an International Journal
Rough sets and gradual decision rules
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Application of fuzzy preference based rough set model to condition monitoring
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
On topological dominance-based rough set approach
Transactions on rough sets XII
A multi-objective genetic algorithm approach to rule mining for affective product design
Expert Systems with Applications: An International Journal
A new proposal for fuzzy rough approximations and gradual decision rule representation
Transactions on Rough Sets II
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Dominance-based rough set approach is an extension of the basic rough set approach proposed by Pawlak, to multicriteria classification problems. In this paper, the dominance-based rough set approach is considered in the context of vague information on preferences and decision classes. The vagueness is handled by possibility and necessity measures defined using modifiers of fuzzy sets. Due to this way of handling the vagueness, the lower and upper approximations of preference-ordered decision classes are fuzzy sets whose membership functions are necessity and possibility measures, respectively.