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Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion

Dempster-Shafer (DS) evidence theory is widely used in various fields of uncertain information processing, but it may produce counterintuitive results when dealing with conflicting data. Therefore, this paper proposes a new data fusion method which combines the Deng entropy and the negation of basic...

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Autores principales: Chen, Yutong, Tang, Yongchuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8066141/
https://www.ncbi.nlm.nih.gov/pubmed/33800628
http://dx.doi.org/10.3390/e23040402
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author Chen, Yutong
Tang, Yongchuan
author_facet Chen, Yutong
Tang, Yongchuan
author_sort Chen, Yutong
collection PubMed
description Dempster-Shafer (DS) evidence theory is widely used in various fields of uncertain information processing, but it may produce counterintuitive results when dealing with conflicting data. Therefore, this paper proposes a new data fusion method which combines the Deng entropy and the negation of basic probability assignment (BPA). In this method, the uncertain degree in the original BPA and the negation of BPA are considered simultaneously. The degree of uncertainty of BPA and negation of BPA is measured by the Deng entropy, and the two uncertain measurement results are integrated as the final uncertainty degree of the evidence. This new method can not only deal with the data fusion of conflicting evidence, but it can also obtain more uncertain information through the negation of BPA, which is of great help to improve the accuracy of information processing and to reduce the loss of information. We apply it to numerical examples and fault diagnosis experiments to verify the effectiveness and superiority of the method. In addition, some open issues existing in current work, such as the limitations of the Dempster-Shafer theory (DST) under the open world assumption and the necessary properties of uncertainty measurement methods, are also discussed in this paper.
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spelling pubmed-80661412021-04-25 Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion Chen, Yutong Tang, Yongchuan Entropy (Basel) Article Dempster-Shafer (DS) evidence theory is widely used in various fields of uncertain information processing, but it may produce counterintuitive results when dealing with conflicting data. Therefore, this paper proposes a new data fusion method which combines the Deng entropy and the negation of basic probability assignment (BPA). In this method, the uncertain degree in the original BPA and the negation of BPA are considered simultaneously. The degree of uncertainty of BPA and negation of BPA is measured by the Deng entropy, and the two uncertain measurement results are integrated as the final uncertainty degree of the evidence. This new method can not only deal with the data fusion of conflicting evidence, but it can also obtain more uncertain information through the negation of BPA, which is of great help to improve the accuracy of information processing and to reduce the loss of information. We apply it to numerical examples and fault diagnosis experiments to verify the effectiveness and superiority of the method. In addition, some open issues existing in current work, such as the limitations of the Dempster-Shafer theory (DST) under the open world assumption and the necessary properties of uncertainty measurement methods, are also discussed in this paper. MDPI 2021-03-28 /pmc/articles/PMC8066141/ /pubmed/33800628 http://dx.doi.org/10.3390/e23040402 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Chen, Yutong
Tang, Yongchuan
Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion
title Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion
title_full Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion
title_fullStr Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion
title_full_unstemmed Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion
title_short Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion
title_sort measuring the uncertainty in the original and negation of evidence using belief entropy for conflict data fusion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8066141/
https://www.ncbi.nlm.nih.gov/pubmed/33800628
http://dx.doi.org/10.3390/e23040402
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