Results 21 to 30 of about 7,149 (239)
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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A Weighted Belief Entropy-Based Uncertainty Measure for Multi-Sensor Data Fusion. [PDF]
Sensors (Basel), 2017 In real applications, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. In this paper, in the frame of Dempster–Shafer evidence theory, a weighted belief entropy based on Deng entropy is proposed to quantify the uncertainty of uncertain information.
Tang Y, Zhou D, Xu S, He Z.
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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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Fractal-based belief entropy [PDF]
Information Sciences, 2022 The total uncertainty measurement of basic probability assignment (BPA) in Dempster-Shafer evidence theory (DSET) has always been an open issue. Although some scholars put forward various measurements and entropies of BPA, due to the existence of discord and non-specificity, there is no method can measure BPA reasonably.
Zhou, Qianli, Deng, Yong
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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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Mathematics, 2020 The Dempster–Shafer evidence theory has been widely applied in the field of information fusion. However, when the collected evidence data are highly conflicting, the Dempster combination rule (DCR) fails to produce intuitive results most of the time.
Dingyi Gan, Bin Yang, Yongchuan Tang
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