AGGREGATION IN FUZZY FAULT TREE QUANTIFICATION: COMPARISON OF MEANS AND EXPERTONS TECHNIQUES
Mots-clés :
Fuzzy Fault Tree Quantification, Aggregation, Arithmetic Mean, ExpertonRésumé
This paper presents a comparison of the two techniques: arithmetic means and expertons, used for aggregation of experts’ judgments relative to basic events of fault trees. Valuations as confidence intervals included in [0, 1] have been considered. First, bounds are numbers to one decimal; next, numbers belonging to [0, 1]. In this last case, R+_expertons concept is used, with a counter-expertise form proposed. The means technique is well known in practice, but as fault tree is a logical diagram built by "AND" and "OR" gates, i.e. nonlinear operators, its use leads to wrong results and expertons technique should be used.Téléchargements
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