Results 1 to 10 of about 303 (162)

A New Belief Entropy to Measure Uncertainty of Basic Probability Assignments Based on Belief Function and Plausibility Function

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
doaj   +3 more sources

An Improved Belief Entropy to Measure Uncertainty of Basic Probability Assignments Based on Deng Entropy and Belief Interval

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, Duofa Ji, Xiaodong Yang, Liguo Fei, Changhai Zhai   +4 more
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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

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, Deyun Zhou, Yongchuan Tang, Xiaoyang Li, Jichuan Huang   +4 more
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Generalized Belief Entropy and Its Application in Identifying Conflict Evidence

IEEE Access, 2019
Dempster-Shafer evidence theory has wide applications in many fields. Recently, A new entropy called Deng entropy was proposed in evidence theory. Some scholars have pointed out that Deng Entropy does not satisfy the additivity in uncertain measurements.
Fan Liu, Xiaozhuan Gao, Jie Zhao, Yong Deng   +3 more
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Improved Base Belief Function-Based Conflict Data Fusion Approach Considering Belief Entropy in the Evidence Theory

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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Evidential Decision Tree Based on Belief Entropy

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
doaj   +3 more sources

An Improved Multi-Source Data Fusion Method Based on the Belief Entropy and Divergence Measure

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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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, Yi Hou, Xinpu Deng, Kewei Ouyang, Ye Zhang, Shilin Zhou   +5 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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Forecasting Using Information and Entropy Based on Belief Functions

Complexity, 2020
This paper introduces an entropy-based belief function to the forecasting problem. While the likelihood-based belief function needs to know the distribution of the objective function for the prediction, the entropy-based belief function does not. This is
Woraphon Yamaka, Songsak Sriboonchitta
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