摘要
覆盖粗糙集作为经典粗糙集一种较为流行的扩充模型,其现有不确定性度量方法主要包括覆盖粒度、粗糙度、粗糙熵、模糊度和模糊熵等。本文从纯粗糙集、信息论和模糊性三个视角对覆盖粗糙集的不确定性度量方法进行了分类梳理,通过结合覆盖粒度对覆盖粗糙度、覆盖精确度和覆盖粗糙熵进行了修正定义;设计了基于最小描述交的隶属函数,结合隶属函数对覆盖模糊度和覆盖模糊熵重新定义,给出了相关推论,分析了相关性质,为后续研究覆盖粗糙集不确定性的相关问题提供了新思路。
Covering-based rough sets is a popular extension model of classical rough sets,and its existing uncertainty measurement methods mainly include covering granularity,roughness,rough entropy,ambiguity and fuzzy entropy.This paper classified and sorted the uncertainty measurement method of covering rough sets from three aspects:pure rough set,information theory and fuzziness.First,we defined the membership function based on the minimal description.Then,combined with the proposed membership function,we redefined the covering ambiguity and the covering fuzzy entropy respectively.The relevant inferences and properties are analyzed.Those results may provide an idea for the follow-up research on the uncertainty of the covering-based rough sets.
作者
凌敏
刘财辉
LING Min;LIU Cai-hui(School of Mathematics and Computer Science,Gannan Normal University,Ganzhou 341000,China)
出处
《模糊系统与数学》
北大核心
2023年第1期100-108,共9页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(62166001)
江西省自然科学基金面上项目(20202BAB202010)
关键词
覆盖粗糙集
粗糙度
粗糙熵
模糊度
模糊熵
Covering Rough Sets
Roughness
Roughness Entropy
Fuzziness
Fuzzy Entropy
