摘要：This issue of tweets will introduce the 6.3 comparative analysis of the intensive reading journal paper "MARCOs-based two-dimensio
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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6.3对比分析”。
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Dear, this is the LearingYard Academy!
Today, the editor brings the "the 6.3 comparative analysis 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6.3对比分析。
This issue of tweets will introduce the 6.3 comparative analysis 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）
为了说明本文提出方法的有效性和优越性，在此部分内容中将本文方法和其他2种方法进行了对比。由于前文第三章内容提到二维语言直觉变量 可以转换为二维不确定语言，因此选择了二维不确定语言幂广义加权平均算子（2DULPGWA），二维不确定语言广义加权平均算子（2DULGWA），TODIM方法以及IS方法，进行对比分析。在用不同方法对本文算例进行排序之后，作者进行了结果及其原因分析。
In order to illustrate the effectiveness and superiority of the proposed method, the proposed method is compared with other two methods in this part. Since it IS mentioned in the third chapter above that the intuitive variables of two-dimensional language can be converted into two-dimensional uncertain language, the power generalized weighted average operator of two-dimensional uncertain language (2DULPGWA), generalized weighted average operator of two-dimensional uncertain language (2DULGWA), TODIM method and IS method are selected for comparative analysis. After sorting the examples in this paper by different methods, the author analyzes the results and the reasons.
本文的方法和2DULPGWA以及2DULGWA算子的排序结果略有不同，其主要原因是因为两个方法使用了不同的运算法则。和TOPSIS以及TODIM方法相比，两者的排序结果一致，和本文的方法相比两者各有优势，但本文的方法在计算量方面会更小。
The sorting results of the method in this paper are slightly different from those of 2DULPGWA and 2DULGWA operator, mainly because the two methods use different algorithms. Compared with TOPSIS and TODIM methods, the sorting results of the two methods are consistent, and both have advantages compared with the method in this paper, but the method in this paper will be smaller in terms of computation.
四、知识补充——2DULPGWA和2DULGWA算子（Knowledge Supplement - 2DULPGWA and 2DULGWA operators）
（一）2DULPGWA算子
(一) 2DULPGWA operator
（二）2DULGWA算子
(二) 2DULGWA operator
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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：
[1] 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.
[2] 王琪, 卢美顺. 考虑决策者有限性心理行为的应急物资运输动态决策方法 [J]. 上海管理科学, 2021, 43(4): 95-102.
[3] Liu Peide, Wang Yumei. The aggregation operators based on the 2-dimension uncertain linguistic information and their application to decision making [J]. International Journal of Machine Learning and Cybernetics, 2016, 7(1): 1057-1074.
本文由LearningYard学苑整理并发出，如有侵权请在后台留言！
文案| Ann
排版| Ann
审核| Whisper
来源：LearningYard学苑