面向集值决策系统的集值模糊粒球粗糙集模型与属性约简算法

doi:10.16451/j.cnki.issn1003-6059.202512002

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Abstract As an effective multi-granularity data processing paradigm, granular ball computing(GBC) exhibits significant potential in the fields of complex data analysis and knowledge reduction. However, existing GBC models fail to fully characterize the fuzziness and uncertainty inherent in set-valued attributes, restricting their application in set-valued decision systems. To address this limitation, a set-valued fuzzy granular ball rough set model is proposed and a corresponding attribute reduction algorithm is designed. Firstly, an adaptive granular ball generation algorithm is proposed to enable the dynamic granulation of the data space based on the characteristics of set-valued data. Secondly, fuzzy granular ball tolerance relations and approximation operators are introduced, and their mathematical properties are systematically analyzed and proven. Furthermore, a forward greedy attribute reduction algorithm is constructed based on dependency degree to achieve efficient attribute reduction. Finally, experimental results demonstrate that the proposed algorithm not only obtains more compact attribute reducts but also achieves higher average classification accuracy with CART and SVM classifiers. These results validate its effectiveness and superiority in set-valued decision systems.

Key words： Set-Valued Data Granular Ball Computing Fuzzy Rough Set Dependency Degree Attribute Reduction

Received: 19 November 2025

ZTFLH:

TP18

Fund:National Natural Science Foundation of China(No.12571497,12371466), Discipline Construction Program of Zhejiang Province under Grant(No.1106406022102)

Corresponding Authors: GU Shenming, Master, professor. His research interests include rough sets, granular computing, and deep learning.

About author:: LUO Zhongtuan, Master student. Her research interests include rough sets and granular computing.
TAN Anhui, Ph.D., professor. His research interests include granular computing, uncertain data processing, and intelligent com-puting.
WU Weizhi, Ph.D., professor. His research interests include rough sets, granular computing, data mining, and artificial intelligence.

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Cite this article:

LUO Zhongtuan,TAN Anhui,GU Shenming等. Set-Valued Fuzzy Granular Ball Rough Set Model and Attribute Reduction Algorithm for Set-Valued Decision Systems[J]. Pattern Recognition and Artificial Intelligence, 2025, 38(12): 1075-1090.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202512002 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2025/V38/I12/1075

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