Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)

A New Preprocessing Method on Evidence Weight of Dempster Fusion Rule

Authors
Yingchun Li, Wei Xiong, Desheng Liu, JianBo Cheng
Corresponding Author
Yingchun Li
Available Online April 2017.
DOI
10.2991/fmsmt-17.2017.240How to use a DOI?
Keywords
D-S evidence theory, Fusion rule, Belief mass, Evidence weight, Reassignment
Abstract

In allusion to the three problems of conventional D-S (Dempster-Shafer) evidence theory, this paper proposes an improved Dempster fusion rule based on weight preprocessing. By comparing the fusion results with conventional method and other improved methods, we conclude that the method in this paper is more superior in dealing with uncertainty, and more reasonable in processing the evidence weight.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/fmsmt-17.2017.240
ISSN
2352-5401
DOI
10.2991/fmsmt-17.2017.240How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yingchun Li
AU  - Wei Xiong
AU  - Desheng Liu
AU  - JianBo Cheng
PY  - 2017/04
DA  - 2017/04
TI  - A New Preprocessing Method on Evidence Weight of Dempster Fusion Rule
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 1226
EP  - 1230
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.240
DO  - 10.2991/fmsmt-17.2017.240
ID  - Li2017/04
ER  -