Name
Abstract | ||
|---|---|---|
Dempster-Shafer evidence theory is widely used in the field of information fusion especially when confronting with uncertainties. However, Dempster’s rule of combination may lead to counter-intuitive results when dealing with highly conflicting bodies of evidence (BOEs). Numerous methods were proposed to address this problem. Enlightened by the research of interaction among nodes in complex networks, this paper study the combination of evidences from the perspective of networks: BOEs are regarded as nodes, the conflicting degree between BOEs is considered as one possible interaction between nodes. The direct and indirect interactions among nodes in networks are considered together to determine the weights of the BOEs. After process of weighted average, the modified BOEs can be efficiently combined by Dempster’s rule of combination. A numerical example is illustrated to show the use and better performance of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.ins.2021.08.088 | Information Sciences |
Keywords | DocType | Volume |
Evidence theory,Sensor data fusion,Distance function,Networks | Journal | 580 |
ISSN | Citations | PageRank |
0020-0255 | 3 | 0.40 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leihui Xiong | 1 | 3 | 0.40 |
| Xiaoyan Su | 2 | 122 | 7.83 |
| Hong Qian | 3 | 9 | 6.22 |