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Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory [PDF]
Entropy, 2022 Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to
Ying Lv +5 more
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Evaluating High-Variance Leaves as Uncertainty Measure for Random Forest Regression [PDF]
Molecules, 2021 Uncertainty measures estimate the reliability of a predictive model. Especially in the field of molecular property prediction as part of drug design, model reliability is crucial.
Thomas-Martin Dutschmann, Knut Baumann
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An Improved Total Uncertainty Measure in the Evidence Theory and Its Application in Decision Making [PDF]
Entropy, 2020 Dempster–Shafer evidence theory (DS theory) has some superiorities in uncertain information processing for a large variety of applications. However, the problem of how to quantify the uncertainty of basic probability assignment (BPA) in DS theory ...
Miao Qin, Yongchuan Tang, Junhao Wen
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Negation of Pythagorean Fuzzy Number Based on a New Uncertainty Measure Applied in a Service Supplier Selection System [PDF]
Entropy, 2020 The Pythagorean fuzzy number (PFN) consists of membership and non-membership as an extension of the intuitionistic fuzzy number. PFN has a larger ambiguity, and it has a stronger ability to express uncertainty. In the multi-criteria decision-making (MCDM)
Haiyi Mao, Rui Cai
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A Dual Measure of Uncertainty: The Deng Extropy [PDF]
Entropy, 2020 The extropy has recently been introduced as the dual concept of entropy. Moreover, in the context of the Dempster–Shafer evidence theory, Deng studied a new measure of discrimination, named the Deng entropy.
Francesco Buono, Maria Longobardi
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A New Total Uncertainty Measure from A Perspective of Maximum Entropy Requirement [PDF]
Entropy, 2021 The Dempster-Shafer theory (DST) is an information fusion framework and widely used in many fields. However, the uncertainty measure of a basic probability assignment (BPA) is still an open issue in DST. There are many methods to quantify the uncertainty
Yu Zhang +3 more
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Negation of Belief Function Based on the Total Uncertainty Measure [PDF]
Entropy, 2019 The negation of probability provides a new way of looking at information representation. However, the negation of basic probability assignment (BPA) is still an open issue.
Kangyang Xie, Fuyuan Xiao
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Entropy, 2023 Dempster–Shafer evidence theory is widely used to deal with uncertain information by evidence modeling and evidence reasoning. However, if there is a high contradiction between different pieces of evidence, the Dempster combination rule may give a fusion
Yongchuan Tang +4 more
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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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