An Improved Belief Entropy and Its Application in Decision-Making

Uncertainty measure in data fusion applications is a hot topic; quite a few methods have been proposed to measure the degree of uncertainty in Dempster-Shafer framework. However, the existing methods pay little attention to the scale of the frame of discernment (FOD), which means a loss of informati...

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Main Authors: Deyun Zhou, Yongchuan Tang, Wen Jiang
Format: Article
Language:English
Published: Wiley 2017-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2017/4359195
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author Deyun Zhou
Yongchuan Tang
Wen Jiang
author_facet Deyun Zhou
Yongchuan Tang
Wen Jiang
author_sort Deyun Zhou
collection DOAJ
description Uncertainty measure in data fusion applications is a hot topic; quite a few methods have been proposed to measure the degree of uncertainty in Dempster-Shafer framework. However, the existing methods pay little attention to the scale of the frame of discernment (FOD), which means a loss of information. Due to this reason, the existing methods cannot measure the difference of uncertain degree among different FODs. In this paper, an improved belief entropy is proposed in Dempster-Shafer framework. The proposed belief entropy takes into consideration more available information in the body of evidence (BOE), including the uncertain information modeled by the mass function, the cardinality of the proposition, and the scale of the FOD. The improved belief entropy is a new method for uncertainty measure in Dempster-Shafer framework. Based on the new belief entropy, a decision-making approach is designed. The validity of the new belief entropy is verified according to some numerical examples and the proposed decision-making approach.
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spelling doaj-art-be2ee8dc2c2d4ef59360f8c005d04b172025-08-20T03:23:31ZengWileyComplexity1076-27871099-05262017-01-01201710.1155/2017/43591954359195An Improved Belief Entropy and Its Application in Decision-MakingDeyun Zhou0Yongchuan Tang1Wen Jiang2School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaUncertainty measure in data fusion applications is a hot topic; quite a few methods have been proposed to measure the degree of uncertainty in Dempster-Shafer framework. However, the existing methods pay little attention to the scale of the frame of discernment (FOD), which means a loss of information. Due to this reason, the existing methods cannot measure the difference of uncertain degree among different FODs. In this paper, an improved belief entropy is proposed in Dempster-Shafer framework. The proposed belief entropy takes into consideration more available information in the body of evidence (BOE), including the uncertain information modeled by the mass function, the cardinality of the proposition, and the scale of the FOD. The improved belief entropy is a new method for uncertainty measure in Dempster-Shafer framework. Based on the new belief entropy, a decision-making approach is designed. The validity of the new belief entropy is verified according to some numerical examples and the proposed decision-making approach.http://dx.doi.org/10.1155/2017/4359195
spellingShingle Deyun Zhou
Yongchuan Tang
Wen Jiang
An Improved Belief Entropy and Its Application in Decision-Making
Complexity
title An Improved Belief Entropy and Its Application in Decision-Making
title_full An Improved Belief Entropy and Its Application in Decision-Making
title_fullStr An Improved Belief Entropy and Its Application in Decision-Making
title_full_unstemmed An Improved Belief Entropy and Its Application in Decision-Making
title_short An Improved Belief Entropy and Its Application in Decision-Making
title_sort improved belief entropy and its application in decision making
url http://dx.doi.org/10.1155/2017/4359195
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