A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information
Authors
Fang Liu, Yanxue Wang
Corresponding Author
Fang Liu
Available Online January 2018.
- DOI
- 10.2991/macmc-17.2018.67How to use a DOI?
- Keywords
- multi-sensor fusion; evidential conflict; belief entropy; fuzzy preference relations; Dempster-Shafer evidence theory
- Abstract
The multi-sensor data fusion technique plays a significant role in fault diagnosis and in a variety of applications. Conflict management is an open issue in Dempster-Shafer evidence theory. In this paper, a novel multi-sensor data fusion approach is proposed based on the spectral angle cosine function of evidence, belief entropy and group decision fuzzy preference relation analysis. The numerical simulation analyses demonstrate that the improved DS evidence theory available in this paper overcomes the limitations of conventional DS evidence theory, and can realizes more reliable fusion with multi-sensor conflicting information compared to the existing methods.
- Copyright
- © 2018, 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 - Fang Liu AU - Yanxue Wang PY - 2018/01 DA - 2018/01 TI - A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information BT - Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017) PB - Atlantis Press SP - 343 EP - 349 SN - 2352-5401 UR - https://doi.org/10.2991/macmc-17.2018.67 DO - 10.2991/macmc-17.2018.67 ID - Liu2018/01 ER -