计算机科学

计算机科学 ›› 2024, Vol. 51 ›› Issue (8): 83-96.doi: 10.11896/jsjkx.230600185

• 数据库&大数据&数据科学 • 上一篇    下一篇

基于θ算子的多粒度直觉模糊粗糙集模型

郑宇, 薛占熬, 吕明明, 徐久成   

  1. 河南师范大学计算机与信息工程学院 河南 新乡 453000
    智慧商务与物联网技术河南省工程实验室 河南 新乡 453000
  • 收稿日期:2023-06-23 修回日期:2023-11-19 出版日期:2024-08-15 发布日期:2024-08-13
  • 通讯作者: 薛占熬(xuezhanao@163.com)
  • 作者简介:(931801047@qq.com)
  • 基金资助:
    国家自然科学基金(61976082,62076089,62002103);河南省科技攻关项目(182102210078,232102210077);河南省高等学校重点科研项目(24A520019)

Multi-granularity Intuitive Fuzzy Rough Set Model Based on θ Operator

ZHENG Yu, XUE Zhan’ao, LYU Mingming, XU Jiucheng   

  1. College of Computer and Information Engineering,Henan Normal University,Xinxiang,Henan 453000,China
    Engineering Lab of Intelligence Business & Internet of Things,Xinxiang,Henan 453000,China
  • Received:2023-06-23 Revised:2023-11-19 Online:2024-08-15 Published:2024-08-13
  • About author:ZHENG Yu,born in 1997,master.His main research interests include multi-granularity rough set,fuzzy set,intuitional fuzzy set and so on.
    XUE Zhan’ao,born in 1963,Ph.D,professor.His main research interests includeartificial intelligence,fuzzy set,rough set and so on.
  • Supported by:
    National Science Foundation of China(61976082,62076089,62002103),Key Science and Technology Program of Henan Province,China(182102210078,232102210077) and Key Research Projects of Higher Education Institutions in Henan Province,China(24A520019).

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摘要： 针对在多属性决策中决策者难以在多个属性相互冲突时做出准确判断的问题,文中在直觉模糊近似空间中,首先利用直觉模糊集的隶属度、非隶属度与模糊蕴含算子,提出了基于θ算子和θ*算子的直觉模糊集及其隶属度和非隶属度的概念,并证明了它们的一系列性质。然后,在直觉模糊集与多粒度粗糙集上,定义基于θ算子的多粒度直觉模糊粗糙集的悲观、乐观模型,讨论两种模型的相关性质。最后,给出了基于θ算子的多粒度直觉模糊粗糙集模型的多属性决策算法,将高校引进的人才评价和企业绿色经济供应链的商家评价作为实例进行了分析,同时还与已有方法进行了分析对比,用乐观、悲观模型与已有方法的决策结果的对比证明了所提方法的正确性,并验证了该模型算法的有效性。

关键词: 粗糙集, 直觉模糊集, 蕴含算子, 多粒度, 多属性决策

Abstract: In order to solve the problem that it is difficult for decision makers to make accurate judgment when multiple attributes conflict with each other in the multi-attribute decision making.In the intuitive fuzzy approximation space,this paper firstly uses the membership degree,non-membership degree and fuzzy implication operator of intuitive fuzzy set,and proposes the concepts of membership degree and non-membership degree based on θ operator and θ* operator,and proves a series of properties of them.Then,in the intuitive fuzzy set and the multi-granularity rough set,the pessimistic and optimistic models of theintuitive fuzzy rough set based on θ operator are defined,and the related properties of the two models are discussed.Finally,a multi-attribute decision algorithm based on the multi-granularity intuitive fuzzy rough set model based on θ operator is presented.The evaluation of talents introduced by universities and the evaluation of businesses in the green economy supply chain of enterprises are analyzed as examples.The correctness of the proposed method is proved by comparing the results of the optimistic and pessimistic models with those of the existing methods.The effectiveness of the model algorithm is also verified.

Key words: Rough set, Intuitive fuzzy set, Implication operator, Multi-granularity, Multi-attribute decision-making

中图分类号: 

  • TP181
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