Formation of Consistent Groups of Expert Evidences Based on Dissimilarity Measures in Evidence Theory

The algorithm for dividing the initial set of group expert assessments into subgroups containing homogeneous, consistent estimates has been propose in this paper. The proposed approach allows to distinguish groups of experts, with a “close” opinion, to analyze them in order to develop a final (group) assessment that takes into account the opinions (arguments) of each expert. Metrics of evidence theory characterizing the degree of proximity of expert assessments are taken as a measure of consistency.