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Representing uncertainty regarding satisfaction degrees using possibility distributions

Robin De Mol (UGent) and Guy De Tré (UGent)
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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. Springer International Publishing, 2018. 597–604. Print.
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 (Vol. 641, pp. 597–604). Presented at the 10th Conference of the European-Society-for-Fuzzy-Logic-and-Technology (EUSFLAT), Springer International Publishing.
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.
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.
Vancouver
1.
De Mol R, De Tré G. Representing uncertainty regarding satisfaction degrees using possibility distributions. 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://dx.doi.org/10.1007/978-3-319-66830-7_53},
  volume       = {641},
  year         = {2018},
}

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