How to improve Dempster's combination rule from point of view of random set framework

Yunmin Zhu; X. Rong Li

doi:10.1109/ICCIAS.2006.294089

How to improve Dempster's combination rule from point of view of random set framework

Yunmin Zhu
, X. Rong Li

Sichuan University
University of New Orleans

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The Dempster's combination rule has been widely used recently since it is a convenient and promising method to combine multi-source information with their own confidence degrees/evidences. On the other hand, it has been criticized and debated upon its some counterintuitive behavior and too restrictive requirements. To clarify the theoretical essence of the Dempster's combination rule and provide a direction to solve these problems, the Dempster's combination rule is formulated based on random set theory first. Then, under this framework, all possible combination rules are presented, and these combination rules based on correlated sensor confidence degrees (evidence supports) are proposed. Finally, the optimal Bayes combination rule can be given whenever all necessary priori conditions are available.

Original language	English
Title of host publication	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Publisher	IEEE Computer Society
Pages	51-56
Number of pages	6
ISBN (Print)	1424406056, 9781424406050
DOIs	https://doi.org/10.1109/ICCIAS.2006.294089
State	Published - 2006
Externally published	Yes
Event	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 - Guangzhou, China Duration: 3 Oct 2006 → 6 Oct 2006

Publication series

Name	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Volume	1

Conference

Conference	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Country/Territory	China
City	Guangzhou
Period	3/10/06 → 6/10/06

Access to Document

10.1109/ICCIAS.2006.294089

Cite this

Zhu, Y., & Li, X. R. (2006). How to improve Dempster's combination rule from point of view of random set framework. In 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 (pp. 51-56). Article 4072042 (2006 International Conference on Computational Intelligence and Security, ICCIAS 2006; Vol. 1). IEEE Computer Society. https://doi.org/10.1109/ICCIAS.2006.294089

@inproceedings{626da30290e547e8aa9667802f750f54,

title = "How to improve Dempster's combination rule from point of view of random set framework",

abstract = "The Dempster's combination rule has been widely used recently since it is a convenient and promising method to combine multi-source information with their own confidence degrees/evidences. On the other hand, it has been criticized and debated upon its some counterintuitive behavior and too restrictive requirements. To clarify the theoretical essence of the Dempster's combination rule and provide a direction to solve these problems, the Dempster's combination rule is formulated based on random set theory first. Then, under this framework, all possible combination rules are presented, and these combination rules based on correlated sensor confidence degrees (evidence supports) are proposed. Finally, the optimal Bayes combination rule can be given whenever all necessary priori conditions are available.",

author = "Yunmin Zhu and Li, \{X. Rong\}",

year = "2006",

doi = "10.1109/ICCIAS.2006.294089",

language = "英语",

isbn = "1424406056",

series = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006",

publisher = "IEEE Computer Society",

pages = "51--56",

booktitle = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006",

note = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 ; Conference date: 03-10-2006 Through 06-10-2006",

}

Zhu, Y & Li, XR 2006, How to improve Dempster's combination rule from point of view of random set framework. in 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006., 4072042, 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006, vol. 1, IEEE Computer Society, pp. 51-56, 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006, Guangzhou, China, 3/10/06. https://doi.org/10.1109/ICCIAS.2006.294089

How to improve Dempster's combination rule from point of view of random set framework. / Zhu, Yunmin; Li, X. Rong.
2006 International Conference on Computational Intelligence and Security, ICCIAS 2006. IEEE Computer Society, 2006. p. 51-56 4072042 (2006 International Conference on Computational Intelligence and Security, ICCIAS 2006; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zhu, Yunmin

AU - Li, X. Rong

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N2 - The Dempster's combination rule has been widely used recently since it is a convenient and promising method to combine multi-source information with their own confidence degrees/evidences. On the other hand, it has been criticized and debated upon its some counterintuitive behavior and too restrictive requirements. To clarify the theoretical essence of the Dempster's combination rule and provide a direction to solve these problems, the Dempster's combination rule is formulated based on random set theory first. Then, under this framework, all possible combination rules are presented, and these combination rules based on correlated sensor confidence degrees (evidence supports) are proposed. Finally, the optimal Bayes combination rule can be given whenever all necessary priori conditions are available.

AB - The Dempster's combination rule has been widely used recently since it is a convenient and promising method to combine multi-source information with their own confidence degrees/evidences. On the other hand, it has been criticized and debated upon its some counterintuitive behavior and too restrictive requirements. To clarify the theoretical essence of the Dempster's combination rule and provide a direction to solve these problems, the Dempster's combination rule is formulated based on random set theory first. Then, under this framework, all possible combination rules are presented, and these combination rules based on correlated sensor confidence degrees (evidence supports) are proposed. Finally, the optimal Bayes combination rule can be given whenever all necessary priori conditions are available.

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DO - 10.1109/ICCIAS.2006.294089

M3 - 会议稿件

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SN - 1424406056

SN - 9781424406050

T3 - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

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BT - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

PB - IEEE Computer Society

T2 - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

Y2 - 3 October 2006 through 6 October 2006

ER -

How to improve Dempster's combination rule from point of view of random set framework

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