Results 11 to 20 of about 338,178 (262)
Pruning and measures of uncertainty [PDF]
RAIRO. Informatique théorique, 1978 We introduce a new property, pruning, for measures of uncertainty and investigate its consequences. In particular, we derive a new characterization of the additive, subadditive and symmetric entropies without assuming expansibility. Pruning also provides a new motivation for Hartley's entropy.
B. Forte, SEMPI, Carlo
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Measuring Knightian uncertainty [PDF]
Empirical Economics, 2019 KOF Working Papers ...
Andreas Dibiasi, David Iselin
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Measuring Uncertainty in the Negation Evidence for Multi-Source Information Fusion
Entropy, 2022 Dempster–Shafer evidence theory is widely used in modeling and reasoning uncertain information in real applications. Recently, a new perspective of modeling uncertain information with the negation of evidence was proposed and has attracted a lot of ...
Yongchuan Tang, Yong Chen, Deyun Zhou
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Uncertainty of Interval Type-2 Fuzzy Sets Based on Fuzzy Belief Entropy
Entropy, 2021 Interval type-2 fuzzy sets (IT2 FS) play an important part in dealing with uncertain applications. However, how to measure the uncertainty of IT2 FS is still an open issue.
Sicong Liu, Rui Cai
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Entropy, 2021 Much attention has been paid to construct an applicable knowledge measure or uncertainty measure for Atanassov’s intuitionistic fuzzy set (AIFS). However, many of these measures were developed from intuitionistic fuzzy entropy, which cannot really ...
Xuan Wu, Yafei Song, Yifei Wang
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Uncertainty in Measurement [PDF]
, 2020 Measurements of physical quantities are the corner stone upon which we humans have built the scientific perception of the world. Measurements are the distinctive means to tell the scientific truth apart from any other approach to knowledge. The fundamental concepts of measurement and uncertainty in measurement have been analysed with reference to ...
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Sensors, 2018 Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belief entropy is still an open issue, even a blank field for the open world assumption.
Yongchuan Tang +2 more
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On Measures of Uncertainty in Classification
IEEE Transactions on Signal Processing, 2023 Uncertainty is unavoidable in classification tasks and might originate from data (e.g., due to noise or wrong labeling), or the model (e.g., due to erroneous assumptions, etc). Providing an assessment of uncertainty associated with each outcome is of paramount importance in assessing the reliability of classification algorithms, especially on unseen ...
Saloua Chlaily +3 more
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Entropy, 2019 Uncertain information exists in each procedure of an air combat situation assessment. To address this issue, this paper proposes an improved method to address the uncertain information fusion of air combat situation assessment in the Dempster– ...
Ying Zhou, Yongchuan Tang, Xiaozhe Zhao
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Entropy, 2020 Dempster–Shafer theory has been widely used in many applications, especially in the measurement of information uncertainty. However, under the D-S theory, how to use the belief entropy to measure the uncertainty is still an open issue.
Jiapeng Li, Qian Pan
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