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Representing uncertainty regarding satisfaction degrees using possibility distributions

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Abstract
Evaluating flexible criteria on data leads to degrees of satisfaction. If a datum is uncertain, it can be uncertain to which degree it satisfies the criterion. This uncertainty can be modelled using a possibility distribution over the domain of possible degrees of satisfaction. In this work, we discuss the meaningfulness thereof by looking at the semantics of such a representation of the uncertainty. More specifically, it is shown that defuzzification of such a representation, towards usability in (multi-criteria) decision support systems, corresponds to expressing a clear attitude towards uncertainty (optimistic, pessimistic, cautious, etc.)
Keywords
FUZZY-SETS, SYSTEMS, QUERIES

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MLA
De Mol, Robin, and Guy De Tré. “Representing Uncertainty Regarding Satisfaction Degrees Using Possibility Distributions.” ADVANCES IN FUZZY LOGIC AND TECHNOLOGY 2017, VOL 1, vol. 641, no. 1, Springer International Publishing, 2018, pp. 597–604, doi:10.1007/978-3-319-66830-7_53.
APA
De Mol, R., & De Tré, G. (2018). Representing uncertainty regarding satisfaction degrees using possibility distributions. ADVANCES IN FUZZY LOGIC AND TECHNOLOGY 2017, VOL 1, 641(1), 597–604. https://doi.org/10.1007/978-3-319-66830-7_53
Chicago author-date
De Mol, Robin, and Guy De Tré. 2018. “Representing Uncertainty Regarding Satisfaction Degrees Using Possibility Distributions.” In ADVANCES IN FUZZY LOGIC AND TECHNOLOGY 2017, VOL 1, 641:597–604. Springer International Publishing. https://doi.org/10.1007/978-3-319-66830-7_53.
Chicago author-date (all authors)
De Mol, Robin, and Guy De Tré. 2018. “Representing Uncertainty Regarding Satisfaction Degrees Using Possibility Distributions.” In ADVANCES IN FUZZY LOGIC AND TECHNOLOGY 2017, VOL 1, 641:597–604. Springer International Publishing. doi:10.1007/978-3-319-66830-7_53.
Vancouver
1.
De Mol R, De Tré G. Representing uncertainty regarding satisfaction degrees using possibility distributions. In: ADVANCES IN FUZZY LOGIC AND TECHNOLOGY 2017, VOL 1. Springer International Publishing; 2018. p. 597–604.
IEEE
[1]
R. De Mol and G. De Tré, “Representing uncertainty regarding satisfaction degrees using possibility distributions,” in ADVANCES IN FUZZY LOGIC AND TECHNOLOGY 2017, VOL 1, Warsaw, POLAND, 2018, vol. 641, no. 1, pp. 597–604.
@inproceedings{8564693,
  abstract     = {{Evaluating flexible criteria on data leads to degrees of satisfaction. If a datum is uncertain, it can be uncertain to which degree it satisfies the criterion. This uncertainty can be modelled using a possibility distribution over the domain of possible degrees of satisfaction. In this work, we discuss the meaningfulness thereof by looking at the semantics of such a representation of the uncertainty. More specifically, it is shown that defuzzification of such a representation, towards usability in (multi-criteria) decision support systems, corresponds to expressing a clear attitude towards uncertainty (optimistic, pessimistic, cautious, etc.)}},
  author       = {{De Mol, Robin and De Tré, Guy}},
  booktitle    = {{ADVANCES IN FUZZY LOGIC AND TECHNOLOGY 2017, VOL 1}},
  isbn         = {{9783319668291}},
  issn         = {{2194-5357}},
  keywords     = {{FUZZY-SETS,SYSTEMS,QUERIES}},
  language     = {{eng}},
  location     = {{Warsaw, POLAND}},
  number       = {{1}},
  pages        = {{597--604}},
  publisher    = {{Springer International Publishing}},
  title        = {{Representing uncertainty regarding satisfaction degrees using possibility distributions}},
  url          = {{http://doi.org/10.1007/978-3-319-66830-7_53}},
  volume       = {{641}},
  year         = {{2018}},
}

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