Uncertainty measure in evidence theory
Y Deng - Science China Information Sciences, 2020 - Springer
As an extension of probability theory, evidence theory is able to better handle unknown and
imprecise information. Owing to its advantages, evidence theory has more flexibility and …
imprecise information. Owing to its advantages, evidence theory has more flexibility and …
[HTML][HTML] Representing uncertainty and imprecision in machine learning: A survey on belief functions
Uncertainty and imprecision accompany the world we live in and occur in almost every
event. How to better interpret and manage uncertainty and imprecision play a vital role in …
event. How to better interpret and manage uncertainty and imprecision play a vital role in …
Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy
F **ao - Information Fusion, 2019 - Elsevier
Multi-sensor data fusion technology plays an important role in real applications. Because of
the flexibility and effectiveness in modeling and processing the uncertain information …
the flexibility and effectiveness in modeling and processing the uncertain information …
CEQD: A complex mass function to predict interference effects
F **ao - IEEE Transactions on Cybernetics, 2021 - ieeexplore.ieee.org
Uncertainty is inevitable in the decision-making process of real applications. Quantum
mechanics has become an interesting and popular topic in predicting and explaining human …
mechanics has become an interesting and popular topic in predicting and explaining human …
Information volume of mass function
Y Deng - International Journal of Computers Communications & …, 2020 - univagora.ro
Given a probability distribution, its corresponding information volume is Shannon entropy.
However, how to determine the information volume of a given mass function is still an open …
However, how to determine the information volume of a given mass function is still an open …
Determine the number of unknown targets in open world based on elbow method
Generalized evidence theory as an extension of Dempster-Shafer evidence theory can deal
with uncertain information fusion in the open world. However, one of the open issues is to …
with uncertain information fusion in the open world. However, one of the open issues is to …
A large-scale group consensus reaching approach considering self-confidence with two-tuple linguistic trust/distrust relationship and its application in life cycle …
M Zhou, YQ Zheng, YW Chen, BY Cheng… - Information …, 2023 - Elsevier
Large-scale group decision making (LSGDM) is very common in real world, and especially
how to reach a relatively consensus status in a social network is a hot topic. In this paper, we …
how to reach a relatively consensus status in a social network is a hot topic. In this paper, we …
Deng entropy
Y Deng - Chaos, Solitons & Fractals, 2016 - Elsevier
Dempster Shafer evidence theory has been widely used in many applications due to its
advantages to handle uncertainty. However, how to measure uncertainty in evidence theory …
advantages to handle uncertainty. However, how to measure uncertainty in evidence theory …
A distance measure for intuitionistic fuzzy sets and its application to pattern classification problems
F **ao - IEEE Transactions on Systems, Man, and Cybernetics …, 2019 - ieeexplore.ieee.org
As a generation of fuzzy sets, intuitionistic fuzzy sets (IFSs) have a more powerful ability to
represent and address the uncertainty of information. Therefore, IFSs have been used in …
represent and address the uncertainty of information. Therefore, IFSs have been used in …
A novel quantum model of mass function for uncertain information fusion
X Deng, S Xue, W Jiang - Information Fusion, 2023 - Elsevier
Understanding the uncertainty involved in a mass function is a central issue in Dempster–
Shafer evidence theory for uncertain information fusion. Recent advances suggest to …
Shafer evidence theory for uncertain information fusion. Recent advances suggest to …