A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information

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/).

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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  -