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Dynamic aggregation operators and Einstein operations based on interval-valued picture hesitant fuzzy information and their applications in multi-period decision making
Computational and Applied Mathematics ( IF 2.5 ) Pub Date : 2021-04-29 , DOI: 10.1007/s40314-021-01510-w
Hüseyin Kamacı , Subramanian Petchimuthu , Eyüp Akçetin

The traditional picture hesitant fuzzy aggregation operators are generally suitable for aggregating information acquired in the form of picture hesitant fuzzy numbers, but they will fail in dealing with interval-valued picture hesitant fuzzy information. In this paper, we describe the notion of interval-valued picture hesitant fuzzy set and the operational laws of interval-valued picture hesitant fuzzy variables. Moreover, we derive some dynamic interval-valued picture hesitant fuzzy aggregation operators (based on Einstein operators) to aggregate the interval-valued picture hesitant fuzzy information collected at different periods. Some desirable properties of these aggregation operators are discussed in detail. In addition, we develop the approaches to tackle the multi-period decision-making problems, where all decision information takes the form of interval-valued picture hesitant fuzzy information collected at different periods. In an attempt to illustrate the applications of the proposed approaches, two numerical examples are given to measure the impact of Coronavirus Disease 2019 (COVID-19) in daily life and to identify the optimal investment opportunity. Finally, a comparative analysis of the proposed and existing studies are conducted to demonstrate the effectiveness of the proposed approaches. The presented interval-valued picture hesitant fuzzy operations, aggregation operators, and decision-making approaches can widely apply to dynamic decision analysis and multi-stage decision analysis in real life.



中文翻译:

基于区间值图像犹豫模糊信息的动态聚合算子和爱因斯坦运算及其在多周期决策中的应用

传统的图像犹豫模糊聚合算子通常适合于聚合以图像犹豫模糊数形式获取的信息,但是它们将无法处理区间值的图像犹豫模糊信息。在本文中,我们描述了间隔值图像犹豫模糊集的概念以及间隔值图像犹豫模糊变量的运算规律。此外,我们推导了一些动态的间隔值图像犹豫模糊聚合算子(基于爱因斯坦算子),以聚合在不同时期收集的间隔值图像犹豫模糊信息。这些聚合运算符的一些理想属性将详细讨论。此外,我们还开发了解决多期决策问题的方法,其中所有决策信息均采用在不同时期收集的间隔值图像犹豫模糊信息的形式。为了说明所提出方法的应用,给出了两个数值示例来测量冠状病毒病2019(COVID-19)在日常生活中的影响并确定最佳投资机会。最后,对提议的和现有的研究进行了比较分析,以证明提议的方法的有效性。提出的区间值图像犹豫模糊运算,聚合算子和决策方法可广泛应用于现实生活中的动态决策分析和多阶段决策分析。为了说明所提出方法的应用,给出了两个数值示例来测量冠状病毒病2019(COVID-19)在日常生活中的影响并确定最佳投资机会。最后,对提议的和现有的研究进行了比较分析,以证明提议的方法的有效性。提出的区间值图像犹豫模糊运算,聚合算子和决策方法可广泛应用于现实生活中的动态决策分析和多阶段决策分析。为了说明所提出方法的应用,给出了两个数值示例来测量冠状病毒病2019(COVID-19)在日常生活中的影响并确定最佳投资机会。最后,对提议的和现有的研究进行了比较分析,以证明提议的方法的有效性。提出的区间值图像犹豫模糊运算,聚合算子和决策方法可广泛应用于现实生活中的动态决策分析和多阶段决策分析。对提议的和现有的研究进行了比较分析,以证明提议的方法的有效性。提出的区间值图像犹豫模糊运算,聚合算子和决策方法可广泛应用于现实生活中的动态决策分析和多阶段决策分析。对提议的和现有的研究进行了比较分析,以证明提议的方法的有效性。提出的区间值图像犹豫模糊运算,聚合算子和决策方法可广泛应用于现实生活中的动态决策分析和多阶段决策分析。

更新日期:2021-04-29
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