Information fusion is an important part of multiple-attribute decision-making, and aggregation operator is an important tool of decision information fusion. Integration operators in a variety of fuzzy information environments have a slight lack of consideration for the correlation between variables. Archimedean copula provides information fusion patterns that rely on the intrinsic relevance of information. This paper extends the Archimedean copula to the aggregation of hesitant fuzzy information. Firstly, the Archimedean copula is used to generate the operation rules of the hesitant fuzzy elements. Secondly, the hesitant fuzzy copula Bonferroni mean operator and hesitant fuzzy weighted copula Bonferroni mean operator are propounded, and several properties are proved in detail. Furthermore, a decision-making method based on the operators is proposed, and the specific decision steps are given. Finally, an example is presented to illustrate the practical advantages of the method, and the sensitivity analysis of the decision results with the change of parameters is carried out.

中文翻译：

---

基于阿基米德Copula的犹豫模糊广义Bonferroni均值算子用于多属性决策

信息融合是多属性决策的重要组成部分，聚合算子是决策信息融合的重要工具。各种模糊信息环境中的积分算子对变量之间的相关性几乎没有考虑。阿基米德系动词提供了依赖于信息的内在关联性的信息融合模式。本文将Archimedean copula扩展到犹豫的模糊信息的聚集。首先，用阿基米德系动词生成犹豫模糊元素的运算规则。其次，提出了犹豫的模糊copula Bonferroni均值算子和犹豫的模糊加权copula Bonferroni均值算子，并详细证明了一些性质。此外，提出了一种基于算子的决策方法，并给出了具体的决策步骤。最后，以一个实例来说明该方法的实际优势，并随着参数的变化对决策结果进行敏感性分析。