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首页> 外文期刊>International journal of machine learning and cybernetics >Multigranulation rough set model in hesitant fuzzy information systems and its application in person-job fit
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Multigranulation rough set model in hesitant fuzzy information systems and its application in person-job fit

机译：犹豫不决模糊信息系统中的多个人粗糙集模型及其在人工工作中的应用

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摘要

Person-job fit is a significant issue in the variety of critical business intelligence applications that aims to match suitable professional abilities with job demands for each job seeker, and many studies based on fuzzy sets have been developed on this topic. Among different types of fuzzy sets, hesitant fuzzy sets are usually utilized to handle situations in which experts hesitate among several values to evaluate an alternative. Recently, various hesitant fuzzy decision making methods have been established, but none of them can be used to solve group decision making problems by means of the multigranulation rough set model and the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) approach. Thus, to solve problems of hesitant fuzzy information analysis and group decision making for person-job fit, we construct a new multigranulation rough set model, named hesitant fuzzy multigranulation rough sets, through combining hesitant fuzzy sets with multigranulation rough sets. Then in order to express the decision making knowledge base more reasonably, we extend the proposed model from single universe to two universes. At last, by utilizing the TODIM approach, we propose a general decision making method that is applied to person-job fit, and the effectiveness of the proposed decision making method is demonstrated by a case study.
机译：人员 - 职位适合是各种关键商业智能应用中的一个重要问题，旨在与每个求职者的工作需求相匹配，以及基于模糊集的许多研究已经开发出这个主题。在不同类型的模糊集中，犹豫不决的模糊集通常用于处理专家在几个值之间犹豫不决的情况，以评估替代方案。最近，已经建立了各种犹豫了模糊决策方法，但是它们都不可用于通过多个人粗糙集模型和Todim（葡萄牙语互动和多标准决策中的葡萄牙语缩写）来解决群组决策问题方法。因此，为了解决犹豫不决的模糊信息分析和群体决策的问题，我们构建了一种新的多个人粗糙集模型，命名为犹豫不决的模糊多个人粗糙集，通过组合犹豫不决的模糊套与多金属粗糙集。然后为了更合理地表达决策，我们将拟议的模型扩展到两个宇宙。最后，通过利用TODIM方法，我们提出了一种施加对人职能的一般决策方法，并通过案例研究证明了所提出的决策方法的有效性。

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