In risk assessment problems, multiple experts are often involved. On many occasions, assessment experts cannot give crisp scores even if there are scoring standards because of limitation and uncertainty. It is reasonable that the assessment data are expressed in the form of interval numbers with self-confidence. A fuzzy risk assessment model based on interval numbers with self-confidence is proposed in this paper. First, a multi-expert interval numbers with self-confidence fusion model is constructed. In the model, experts weights are determined based on subjective weights and objective weights, and the objective weights are calculated based on the length of the base of interval number and self-confidence simultaneously. Second, a novel method determining the symbolic proportion in an assessment distribution is proposed. This method integrates the concept of similarity measure between generalized fuzzy numbers and the length of the base of intersection of fuzzy numbers. Some properties of the proposed symbolic proportion measure are proved. Third, a fuzzy risk assessment model is proposed based on the fuzzy inference system. The output of the model is a distribution with the possible risk ranks and corresponding symbolic proportions. Finally, an illustrative example which shows the proposed fuzzy risk assessment model effective is demonstrated.

中文翻译：

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基于区间数和评估分布的模糊风险评估

在风险评估问题中，经常涉及多个专家。在很多情况下，由于存在局限性和不确定性，即使有评分标准，评估专家也无法给出清晰的分数。可以自信地以区间数的形式表示评估数据。提出了一种基于区间数的自信心模糊风险评估模型。首先，建立了具有自信心融合模型的多专家区间数。该模型基于主观权重和客观权重确定专家权重，同时基于区间数和自信基数的长度计算客观权重。其次，提出了一种确定评估分布中符号比例的新方法。该方法整合了广义模糊数与模糊数交点的基部长度之间的相似性度量概念。证明了所提出的符号比例测度的一些性质。第三，提出了基于模糊推理系统的模糊风险评估模型。该模型的输出是具有可能的风险等级和相应的符号比例的分布。最后，通过一个例子说明了所提出的模糊风险评估模型的有效性。该模型的输出是具有可能的风险等级和相应的符号比例的分布。最后，通过一个例子说明了所提出的模糊风险评估模型的有效性。该模型的输出是具有可能的风险等级和相应的符号比例的分布。最后，通过一个例子说明了所提出的模糊风险评估模型的有效性。