Dempster-Shafer evidence theory is efficient to deal with uncertain information. However,
the traditional basic probability assignment (BPA) only considers the support degree of the …

… The kernel of the approach is an evidential reasoning algorithm developed on the basis of
the DS theory, which is known as the theory of the belief functions. The evidential reasoning …

… Chin et al 43 Weighting for attributes Evidential reasoning approach An evidential reasoning…
Adaptive consensus method The experts' weights are obtained by an adaptive consensus …

… on full consensus without considering consensus reaching efficiency in real decision-making
scenario. Consequently, feedback mechanisms based on soft consensus model have been …

… Based on EK-NN and FEK-NN approaches, a fuzzy evidential reasoning associated nearest
neighbor (FE-NN) algorithm was introduced in [27] with an adaptive neighbor selection, …

… To solve this problem, this paper extends SLIM with the Evidential Reasoning (ER) approach.
In the ER-SLIM model, the belief degrees of the experts are aggregated and HEP can be …

… Independent of concerns about reputation and self-image maintenance, evidential reasoning
… , a theory of reputational concerns and evidential reasoning is better equipped to explain …

… consensus among the various sensors. The fusion process is based upon evidential reasoning
… the fusion results and the degree of consensus between the individual sensor data and …

… This seems reasonable if we assume that an expert consensus is an informed average
opinion. But how reasonable are averages? We must be careful because statistical pathologies …

… method is proposed under the framework of the evidential reasoning (ER) rule with three …
inputs and outputs is embedded into evidence representation for better extracting knowledge …