Evidential Information Fusion on Possibilistic Structure

• URL: http://arxiv.org/abs/2605.17038v1
• Date: Sat, 16 May 2026 15:18:59 GMT
• Title: Evidential Information Fusion on Possibilistic Structure
• Abstract summary: We propose a reversible transformation between belief functions and a possibilistic structure defined on the power set.<n>We then introduce the triangular norm family to develop a general and adaptive evidential information fusion framework.<n>Unlike fusion methods rooted in Dempster semantics, the proposed framework supports more flexible combination behaviors.
• Score: 53.34037686489798
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Dempster's rule is a fundamental tool for combining belief functions from distinct and reliable sources. However, its intersection-based semantics imposes strong structural restrictions, which limits its flexibility in handling complex source states and diverse information fusion scenarios. To overcome this limitation, we propose a reversible transformation, derived from the isopignistic principle, between belief functions and a possibilistic structure defined on the power set. In this transformation, the relationships among subsets are explicitly characterized by a belief evolution network, which provides a more flexible representation of evidential information beyond the conventional mass function structure. On this basis, we further introduce the triangular norm family to develop a general and adaptive evidential information fusion framework. Unlike fusion methods rooted in Dempster semantics, the proposed framework supports more flexible combination behaviors and exhibits advantages in non-distinct source fusion, conflict management, parametric combination design, and heterogeneous information fusion.

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