Name
Abstract | ||
|---|---|---|
This paper presents the MinUnc method to construct m-/belief functions in the framework of the Dempster-Shafer theory to represent the uncertainty in a given body of evidence. Using the Aprinciple of minimum uncertainty and the concepts of entropy and non-specificity, the MinUnc method specifies a partition of a finite interval on the real line and assigns belief masses to the uniform subintervals. The proposed MinUnc method is illustrated using a simple example and applied to uncertainty representation of air flight arrival delay data set. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/FUZZ48607.2020.9177795 | 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) |
Keywords | DocType | ISSN |
Dempster-Shafer theory,Basic belief assignments,Principle of minimum uncertainty,Entropy,Non-Specificity,Predictive belief function | Conference | 1544-5615 |
ISBN | Citations | PageRank |
978-1-7281-6933-0 | 0 | 0.34 |
References | Authors | |
7 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanyan He | 1 | 217 | 25.64 |
| M. Yousuff Hussaini | 2 | 186 | 18.73 |