Sensorial information is very difficult to elicit, to represent and to manage because of its complexity. Fuzzy logic provides an interesting means to deal with such information, since it allows us to represent impreci...Sensorial information is very difficult to elicit, to represent and to manage because of its complexity. Fuzzy logic provides an interesting means to deal with such information, since it allows us to represent imprecise, vague or incomplete descriptions, which are very common in the management of subjective information. Aggregation methods proposed by fuzzy logic are further useful to combine the characteristics of the various components of sensorial information.展开更多
In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used...In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence- theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis- based reliability metrics, possibility-theory-based reliability metrics （posbist reliability） and uncertainty-theory-based reliability metrics （belief reliability）. It is pointed out that a qualified reli- ability metric that is able to consider the effect of epistemic uncertainty needs to （ 1 ） compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and （2） satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.展开更多
文摘Sensorial information is very difficult to elicit, to represent and to manage because of its complexity. Fuzzy logic provides an interesting means to deal with such information, since it allows us to represent imprecise, vague or incomplete descriptions, which are very common in the management of subjective information. Aggregation methods proposed by fuzzy logic are further useful to combine the characteristics of the various components of sensorial information.
基金supported by National Natural Science Foundation of China(No.61573043)
文摘In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence- theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis- based reliability metrics, possibility-theory-based reliability metrics （posbist reliability） and uncertainty-theory-based reliability metrics （belief reliability）. It is pointed out that a qualified reli- ability metric that is able to consider the effect of epistemic uncertainty needs to （ 1 ） compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and （2） satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.
