| Title | Evidence Fusion Method Based on Evidence Trust and Exponential Weighting |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Yan, Qifei, Zhou, Yan, Zou, Li, Li, Yanling |
| Conference Name | 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) |
| Keywords | composability, Computing Theory, Computing Theory and Trust, evidence theory, evidence trust degree, exponential weighting, fusion factor, human factors, pubcrawl, Resiliency, Trust |
| Abstract | In order to solve the problems of unreasonable fusion results of high conflict evidence and ineffectiveness of coefficient weighting in classical evidence theory, a method of evidence fusion based on evidence trust degree and exponential weighting is proposed. Firstly, the fusion factor is constructed based on probability distribution function and evidence trust degree, then the fusion factor is exponentially weighted by evidence weight, and then the evidence fusion rule based on fusion factor is constructed. The results show that this method can effectively solve the problems of unreasonable fusion results of high conflict evidence and ineffectiveness of coefficient weighting. It shows that the new fusion method are more reasonable, which provides a new idea and method for solving the problems in evidence theory. |
| DOI | 10.1109/ITNEC48623.2020.9085124 |
| Citation Key | yan_evidence_2020 |
Evidence Fusion Method Based on Evidence Trust and Exponential Weighting