New Evidential Information Fusion Framework Based on Possibilistic Structure
A research paper proposes a novel evidential information fusion framework that overcomes limitations of Dempster's rule. The framework uses a reversible transformation derived from the isopignistic principle, mapping belief functions to a possibilistic structure on the power set. A belief evolution network explicitly characterizes relationships among subsets, enabling more flexible representation. The triangular norm family is introduced to develop a general and adaptive fusion method, supporting more flexible fusion scenarios than traditional Dempster semantics. The paper is published on arXiv with ID 2605.17038.
Key facts
- Dempster's rule is fundamental for combining belief functions from distinct and reliable sources.
- Dempster's rule has strong structural restrictions due to its intersection-based semantics.
- The proposed transformation is reversible and derived from the isopignistic principle.
- The transformation maps between belief functions and a possibilistic structure on the power set.
- A belief evolution network characterizes relationships among subsets.
- The triangular norm family is used to develop a general fusion framework.
- The framework supports more flexible fusion scenarios than Dempster semantics.
- The paper is available on arXiv with ID 2605.17038.
Entities
Institutions
- arXiv