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A new fuzzy linguistic approach to qualitative Cross Impact Analysis

机译:定性交叉影响分析的一种新的模糊语言学方法

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摘要

Scenario Planning helps explore how the possible futures may look like and establishing plans to deal with them, something essential for any company, institution or country that wants to be competitive in this globalize world. In this context, Cross Impact Analysis is one of the most used methods to study the possible futures or scenarios by identifying the system's variables and the role they play in it. In this paper, we focus on the method called MICMAC (Impact Matrix Cross-Reference Multiplication Applied to a Classification), for which we propose a new version based on Computing with Words techniques and fuzzy sets, namely Fuzzy Linguistic MICMAC (FLMICMAC). The new method allows linguistic assessment of the mutual influence between variables, captures and handles the vagueness of these assessments, expresses the results linguistically, provides information in absolute terms and incorporates two new ways to visualize the results. Our proposal has been applied to a real case study and the results have been compared to the original MICMAC, showing the superiority of FLMICMAC as it gives more robust, accurate, complete and easier to interpret information, which can be very useful for a better understanding of the system.
机译:方案规划有助于探索可能的期货,并制定应对方案,这对于任何想要在这个全球化世界中具有竞争力的公司,机构或国家而言都是至关重要的。在这种情况下,交叉影响分析是通过识别系统变量及其在系统中发挥的作用来研究可能的期货或情景的最常用方法之一。在本文中,我们将重点放在称为MICMAC的方法上,为此,我们提出了一种基于单词计算和模糊集的新版本,即模糊语言MICMAC(FLMICMAC)。新方法允许对变量之间的相互影响进行语言评估,捕获并处理这些评估的模糊性,以语言表达结果,以绝对术语提供信息,并结合了两种新方法来可视化结果。我们的建议已应用于实际案例研究,并将结果与​​原始MICMAC进行了比较,显示了FLMICMAC的优越性,因为它可以提供更健壮,准确,完整且易于解释的信息,这对于更好地理解将非常有用系统的。

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