A New Belief Entropy Based on Deng Entropy [PDF]
Entropy, 2019 For Dempster−Shafer evidence theory, how to measure the uncertainty of basic probability assignment (BPA) is still an open question. Deng entropy is one of the methods for measuring the uncertainty of Dempster−Shafer evidence.
Dan Wang, Jiale Gao, Daijun Wei
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An Improved Belief Entropy to Measure Uncertainty of Basic Probability Assignments Based on Deng Entropy and Belief Interval [PDF]
Entropy, 2019 It is still an open issue to measure uncertainty of the basic probability assignment function under Dempster-Shafer theory framework, which is the foundation and preliminary work for conflict degree measurement and combination of evidences.
Yonggang Zhao +4 more
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Improved Base Belief Function-Based Conflict Data Fusion Approach Considering Belief Entropy in the Evidence Theory [PDF]
Entropy, 2020 Due to the nature of the Dempster combination rule, it may produce results contrary to intuition. Therefore, an improved method for conflict evidence fusion is proposed.
Shuang Ni, Yan Lei, Yongchuan Tang
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A modified belief entropy in Dempster-Shafer framework. [PDF]
PLoS ONE, 2017 How to quantify the uncertain information in the framework of Dempster-Shafer evidence theory is still an open issue. Quite a few uncertainty measures have been proposed in Dempster-Shafer framework, however, the existing studies mainly focus on the mass
Deyun Zhou, Yongchuan Tang, Wen Jiang
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Evidential Decision Tree Based on Belief Entropy [PDF]
Entropy, 2019 Decision Tree is widely applied in many areas, such as classification and recognition. Traditional information entropy and Pearson’s correlation coefficient are often applied as measures of splitting rules to find the best splitting attribute ...
Mujin Li, Honghui Xu, Yong Deng
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Uncertainty of Interval Type-2 Fuzzy Sets Based on Fuzzy Belief Entropy [PDF]
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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Belief Entropy Tree and Random Forest: Learning from Data with Continuous Attributes and Evidential Labels [PDF]
Entropy, 2022 As well-known machine learning methods, decision trees are widely applied in classification and recognition areas. In this paper, with the uncertainty of labels handled by belief functions, a new decision tree method based on belief entropy is proposed ...
Kangkai Gao, Yong Wang, Liyao Ma
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A New Belief Entropy in Dempster–Shafer Theory Based on Basic Probability Assignment and the Frame of Discernment [PDF]
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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A New Belief Entropy to Measure Uncertainty of Basic Probability Assignments Based on Belief Function and Plausibility Function [PDF]
Entropy, 2018 How to measure the uncertainty of the basic probability assignment (BPA) function is an open issue in Dempster⁻Shafer (D⁻S) theory.
Lipeng Pan, Yong Deng
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A Novel Belief Entropy for Measuring Uncertainty in Dempster-Shafer Evidence Theory Framework Based on Plausibility Transformation and Weighted Hartley Entropy [PDF]
Entropy, 2019 Dempster-Shafer evidence theory (DST) has shown its great advantages to tackle uncertainty in a wide variety of applications. However, how to quantify the information-based uncertainty of basic probability assignment (BPA) with belief entropy in DST ...
Qian Pan +4 more
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