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今天小编为大家带来「精读期刊论文【基于MARCOS的二维语言直觉多属性群决策方法】的2.2二维语言变量」。
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Share interest, spread happiness,
increase knowledge, and leave beautiful.
Dear, this is the LearingYard Academy!
Today, the editor brings the "the 2.2 two-dimensional language variables of the journal paper 'MARCOs-based two-dimensional language intuitive multi-attribute group decision Method'".
Welcome to visit!
一、内容摘要（Content summary）
本期推文将从思维导图、精读内容、知识补充三个方面介绍精读期刊论文【基于MARCOS的二维语言直觉多属性群决策方法】的2.2二维语言变量。
This issue of tweets will introduce the 2.2 two-dimensional language variables of the intensive reading journal paper "MARCOs-based two-dimensional language intuitive multi-attribute group decision Method" from three aspects: mind mapping, intensive reading content, and knowledge supplement.
二、思维导图（Mind Mapping）
三、精读内容（Detailed Reading Content）
在该部分，作者介绍了二维语言变量的定义，如下所示。
In this p, the author introduces the definition of two-dimensional language variables, as shown below.
二维语言变量是一种用于表示和处理具有双重维度信息的语言评价工具。在决策分析、多属性评价、模糊综合评价等领域中，二维语言变量提供了一种更为丰富和细致的方式来表达评价者的意见和判断。具体来说，二维语言变量由两个部分组成：
Two-dimensional language variables are a language evaluation tool used to represent and process information with dual dimensions. In decision analysis, multi-attribute evaluation, fuzzy comprehensive evaluation and other fields, two-dimensional linguistic variables provide a richer and more detailed way to express the opinions and judgments of the evaluators. Specifically, a two-dimensional language variable consists of two parts:
二维语义信息变量将上述两个维度的信息结合起来，就形成了一个二维语义信息变量。这个变量同时包含了评价者对被评价对象的直接评价以及这个评价的可靠性程度。这样的表示方式使得评价信息更加完整和准确，有助于决策者在进行决策时综合考虑多个方面的因素。
A two-dimensional semantic information variable is formed by combining the above two dimensions of information. This variable includes both the evaluator's direct evaluation of the object being evaluated and the degree of reliability of this evaluation. Such representation makes the evaluation information more complete and accurate, and helps decision makers to consider multiple factors comprehensively when making decisions.
四、知识补充——二维语言变量优缺点（Knowledge supplement -- advantages and disadvantages of two-dimensional language variables）
二维语言变量作为一种评价工具，在多个领域中具有独特的优点和一定的局限性。二维语言变量在表达全面性、提高决策科学性和准确性等方面具有显著优点，但也存在主观性强、量化困难、计算复杂度增加以及依赖特定语境和文化背景等局限性。
As an evaluation tool, two-dimensional language variables have unique advantages and certain limitations in many fields. Two-dimensional language variables have significant advantages in comprehensiveness, scientificity and accuracy of decision making, but they also have limitations such as strong subjectivity, difficulty in quantification, increased computational complexity, and dependence on specific context and cultural background.
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That's all for today's sharing.
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参考资料：ChatGPT、百度百科
参考文献：
许雷, 刘熠, 刘芳等. 基于MARCOS的二维语言直觉多属性群决策方法 [J]. 模糊系统与数学, 2022, 36(5): 128-141.
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文案| Ann
排版| Ann
审核| Whisper
