An Intuitionistic Evidential Method for Weight Determination in FMEA Based on Belief Entropy [PDF]
Entropy, 2019 Failure Mode and Effects Analysis (FMEA) has been regarded as an effective analysis approach to identify and rank the potential failure modes in many applications.
Zeyi Liu, Fuyuan Xiao
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An Improved Belief Entropy in Evidence Theory
IEEE Access, 2020 Uncertainty measurement of the basic probability assignment function has always been a hot issue in Dempster-Shafer evidence. Many existing studies mainly consider the influence of the mass function itself and the size of the frame of discernment, so ...
Hangyu Yan, Yong Deng
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Quantifying Epistemic Uncertainty in Multimodal Long-Tailed Classification: A Belief Entropy-Based Evidential Fusion Framework [PDF]
EntropyDeep multimodal learning has excelled in tasks involving vision, language, and audio modalities. Nevertheless, their performance on tail classes exhibits significant degradation under the long-tailed distributions common in real-world data, meanwhile ...
Guorui Zhu
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An Improved Multi-Source Data Fusion Method Based on the Belief Entropy and Divergence Measure [PDF]
Entropy, 2019 Dempster−Shafer (DS) evidence theory is widely applied in multi-source data fusion technology. However, classical DS combination rule fails to deal with the situation when evidence is highly in conflict.
Zhe Wang, Fuyuan Xiao
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Maximum of Entropy for Belief Intervals Under Evidence Theory [PDF]
IEEE Access, 2020 The Dempster-Shafer Theory (DST) or Evidence Theory has been commonly used to deal with uncertainty. It is based on the basic probability assignment concept (BPA).
Serafin Moral-Garcia, Joaquin Abellan
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Belief Reliability Distribution Based on Maximum Entropy Principle
IEEE Access, 2018 Belief reliability is a new reliability metric based on the uncertainty theory, which aims to measure system performance incorporating the influences from design margin, aleatory uncertainty, and epistemic uncertainty.
Tianpei Zu +3 more
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Interval-valued belief entropies for Dempster–Shafer structures [PDF]
Soft Computing, 2021 In practical application problems, the uncertainty of an unknown object is often very difficult to accurately determine, so Yager proposed the interval-valued entropies for Dempster-Shafer structures, which is based on Dempster-Shafer structures and classic Shannon entropy and is an interval entropy model.
Yige Xue, Yong Deng
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Conflict Management for Target Recognition Based on PPT Entropy and Entropy Distance
Energies, 2021 Conflicting evidence affects the final target recognition results. Thus, managing conflicting evidence efficiently can help to improve the belief degree of the true target.
Shijun Xu +5 more
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Conspiratorial Beliefs Observed through Entropy Principles [PDF]
Entropy, 2015 We propose a novel approach framed in terms of information theory and entropy to tackle the issue of the propagation of conspiracy theories. We represent the initial report of an event (such as the 9/11 terroristic attack) as a series of strings of information, each string classified by a two-state variable Ei = ±1, i = 1, …, N. If the values of the Ei
Golo, Nataša, Galam, Serge
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A New Correlation Measure for Belief Functions and Their Application in Data Fusion
Entropy, 2023 Measuring the correlation between belief functions is an important issue in Dempster–Shafer theory. From the perspective of uncertainty, analyzing the correlation may provide a more comprehensive reference for uncertain information processing.
Zhuo Zhang +3 more
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