The q-rung orthopair fuzzy set (q-ROFS), initiated by Yager, is a novel tool to dispose of indeterminacy that considers the membership $$\mu$$ μ and non-membership $$\nu$$ ν , which satisfy the limited condition $$0\le \mu ^q+\nu ^q\le 1$$ 0 ≤ μ q + ν q ≤ 1 . It can be employed in characterizing the vague preference more precisely and flexibly than intuitionistic fuzzy set and Pythagorean fuzzy set. q-ROFS has attracted deep concern of numerous researchers, which is mainly distributed in diverse research points such as comparison methods, aggregation operators, decision making methods, calculus, information measure, preference relation, graph and application scenarios. As a result of this growth, we give an overview of q-ROFS for offering a clear perspective on novel trends. A total of 80 q-ROFS related publications of Web of Science are in-depth analysis. Some significant results related to annual trends, country level, institutional level, journal level, highly cited papers, and research landscape are generated and illustrated. Eighteen future research directions or challenges related to the q-ROFS theory are indicated. Finally, the co-authorship analysis, the co-citation analysis, the co-occurrence analysis and the bibliographic coupling analysis are derived by VOSviewer software.

中文翻译：

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q-rung orthopair 模糊信息综述：文献计量学和未来方向

Yager 提出的 q-rung orthopair 模糊集 (q-ROFS) 是一种处理不确定性的新工具，它考虑了隶属度 $$\mu$$ μ 和非隶属度 $$\nu$$ ν ，满足有限条件 $$0\le \mu ^q+\nu ^q\le 1$$ 0 ≤ μ q + ν q ≤ 1 。它可以比直觉模糊集和勾股模糊集更精确和灵活地表征模糊偏好。q-ROFS引起了众多研究者的深切关注，主要分布在比较方法、聚合算子、决策方法、微积分、信息测度、偏好关系、图和应用场景等不同的研究点。由于这种增长，我们对 q-ROFS 进行了概述，以提供对新趋势的清晰视角。Web of Science共80篇q-ROFS相关刊物进行了深入分析。生成并说明了与年度趋势、国家层面、机构层面、期刊层面、高被引论文和研究领域相关的一些重要结果。指出了与 q-ROFS 理论相关的 18 个未来研究方向或挑战。最后，通过VOSviewer软件导出合着分析、共被引分析、共现分析和书目耦合分析。