2006/04/11 by Mihai Florea, Jean Dezert, Florea, M. C. +7
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #I.4.8 #Multi-Criteria Decision Making #Rough Sets and Fuzzy Logic
paper · pdf · doi:10.48550/arxiv.cs/0604042
openalex publication_date 2006/04/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents two new promising rules of combination for the fusion of uncertain and potentially highly conflicting sources of evidences in the framework of the theory of belief functions in order to palliate the well-know limitations of Dempster's rule and to work beyond the limits of applicability of the Dempster-Shafer theory. We present both a new class of adaptive combination rules (ACR) and a new efficient Proportional Conflict Redistribution (PCR) rule allowing to deal with highly conflicting sources for static and dynamic fusion applications.