The principle of minimum specificity as a basis for evidential reasoning
Processing and Management of Uncertainty in Knowledge-Based Systems on Uncertainty in knowledge-based systems. International Conference on Information
Stability of linguistic modifiers compatible with a fuzzy logic
Proceedings of the 2nd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems on Uncertainty and intelligent systems
Relative modalities and their use in possibilistic linear programming
Fuzzy Sets and Systems
Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Necessity measures and parametric inclusion relations of fuzzy sets
Fundamenta Informaticae
Dominance-Based Rough Set Approach Using Possibility and Necessity Measures
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
An axiomatic characterization of a fuzzy generalization of rough sets
Information Sciences—Informatics and Computer Science: An International Journal
Ruggedness measures of medical time series using fuzzy-rough sets and fractals
Pattern Recognition Letters
International Journal of Hybrid Intelligent Systems - Hybrid Intelligence using rough sets
Learning fuzzy rules from fuzzy samples based on rough set technique
Information Sciences: an International Journal
Equivalence of Fuzzy-rough Modus Ponens and Fuzzy-rough Modus Tollens
Proceedings of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005
Rough sets and gradual decision rules
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Possibilistic linear programming using general necessity measures preserves the linearity
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
A new proposal for fuzzy rough approximations and gradual decision rule representation
Transactions on Rough Sets II
Hi-index | 0.00 |
In this paper, we propose an approach to possibility and necessity measure specification. This approach is more adequate to human reasoning than direct specification of conjunction and implication functions. Using the proposed approach, a possibility measure is specified by two modifier functions and a strong negation while a necessity measure is specified by two modifier functions only. It is demonstrated that many possibility and necessity measures defined by famous conjunction and implication functions are obtained by the proposed approach. Conditions for specified measures to have good properties are also given. Finally, a simple example of application of possibility and necessity measures to a decision problem is given.