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首页> 美国卫生研究院文献>Computational Intelligence and Neuroscience >An Approach to Linguistic Multiple Attribute Decision-Making Based on Unbalanced Linguistic Generalized Heronian Mean Aggregation Operator
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An Approach to Linguistic Multiple Attribute Decision-Making Based on Unbalanced Linguistic Generalized Heronian Mean Aggregation Operator

机译：基于不平衡语言广义Heronian均值聚合算子的语言多属性决策方法

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摘要

This paper proposes an approach to linguistic multiple attribute decision-making problems with interactive unbalanced linguistic assessment information by unbalanced linguistic generalized Heronian mean aggregation operators. First, some generalized Heronian mean aggregation operators with unbalanced linguistic information are proposed, involving the unbalanced linguistic generalized arithmetic Heronian mean operator and the unbalanced linguistic generalized geometric Heronian mean operator. For the situation that the input arguments have different degrees of importance, the unbalanced linguistic generalized weighted arithmetic Heronian mean operator and the unbalanced linguistic generalized weighted geometric Heronian mean operator are developed. Then we investigate their properties and some particular cases. Finally, the effectiveness and universality of the developed approach are illustrated by a low-carbon tourist instance and comparison analysis. A sensitivity analysis is performed as well to test the robustness of proposed methods.
机译：本文提出了一种基于不平衡语言广义Heronian均值聚合算子的交互式不平衡语言评估信息的语言多属性决策方法。首先，提出了一些具有不平衡语言信息的广义Heronian平均聚合算子，包括不平衡语言广义算术Heronian平均算子和不平衡语言广义几何Heronian平均算子。针对输入自变量具有不同程度的重要性的情况，提出了不平衡的语言广义加权算术Heronian均值算子和不平衡的语言广义加权几何Heronian均值算子。然后，我们研究它们的性质和一些特殊情况。最后，通过低碳旅游实例和比较分析说明了所开发方法的有效性和普遍性。还执行灵敏度分析以测试所提出方法的鲁棒性。

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