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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >Two lambda-correlation coefficients of q-rung orthopair fuzzy sets and their application to clustering analysis
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Two lambda-correlation coefficients of q-rung orthopair fuzzy sets and their application to clustering analysis

机译：Q-rsg orthopair模糊集的两个Lambda相关系数及其在聚类分析中的应用

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摘要

The q-rung orthopair fuzzy set is a significant part of the existing orthopair fuzzy sets, whose advantage is to more comprehensively describe uncertain information. For q-rung orthopair fuzzy sets, the correlation between them is generally measured by the correlation coefficient. In order to express the positive and negative correlations of q-rung orthopair fuzzy sets simultaneously from a statistical perspective, and to reflect the attitude of decision makers, in this paper, two new correlation coefficients of q-rung orthopair fuzzy sets are proposed and investigated. Firstly, a lambda-variance-based correlation coefficient of q-rung orthopair fuzzy sets is proposed from the statistical viewpoint. Secondly, a lambda-matching-function-based correlation coefficient of q-rung orthopair fuzzy sets is defined from the perspective of vector calculation. In the end, an example of clustering analysis is presented to verify the feasibility and superiority of the proposed correlation coefficients by comparing with other existing correlation coefficient of q-rung orthopair fuzzy sets. It can be seen from the clustering results that the two new lambda-correlation coefficients not only consider the positive or negative correlation at the same time, but also can be dynamically adjusted according to the needs of decision makers. Furthermore, clustering results using lambda-variance-based and lambda-matching-function-based correlation coefficients converge faster than clustering results using the existing correlation coefficient in the q-rung orthopair fuzzy environment.
机译：Q-rsg orthopair模糊集是现有的矫形器模糊集的重要组成部分，其优势是更全面地描述不确定的信息。对于Q-RONG Orthopair模糊集合，它们之间的相关性通常通过相关系数来衡量。为了从统计角度表达Q-rsg Orthopair模糊组的正面和负相关性，并反映决策者的态度，在本文中，提出并研究了两个新的Q-rsg orthopair模糊组的相关系数。首先，从统计观点提出了Q-rsg orthopair模糊组的基于Lambda-variance的相关系数。其次，从向量计算的角度定义了Q-rsg orthopair模糊集的λ匹配函数基相关系数。最后，提出了一种聚类分析的示例，以验证所提出的相关系数的可行性和优越性，与Q-rsg orthopair模糊集的其他相关系数进行比较。从聚类结果可以看出，两个新的λ相关系数不仅同时考虑正或负相关，而且可以根据决策者的需求进行动态调整。此外，使用基于Lambda-veriance的基于Lambda-variance和Lambda匹配函数的相关系数的聚类结果比使用Q-rsg Orthopair模糊环境中的现有相关系数的聚类结果更快地收敛。

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