模糊条件熵下模糊β覆盖约简  

Fuzzyβ-covering reduction under fuzzy conditional entropy

作　　者：吴亭毅 林福财 WU Tingyi;LIN Fucai(School of Mathematics and Statistics,Minnan Normal University,Zhangzhou,Fujian 363000,China)

机构地区：[1]闽南师范大学数学与统计学院,福建漳州363000

出　　处：《闽南师范大学学报（自然科学版）》2023年第2期9-16,共8页Journal of Minnan Normal University：Natural Science

基　　金：国家自然科学基金(11571158);福建省自然科学基金重点项目(2020J02043)。

摘　　要：提出模糊β邻域粒结构的信息粒度和信息熵测度,探讨它们在模糊β覆盖决策系统中的应用.首先,将信息测度中的条件熵测度引入模糊β覆盖,以刻画模糊β覆盖决策系统的不确定性.其次,提出一种后向搜索算法来寻找模糊β覆盖族的约简,使其能够删除模糊β覆盖决策表中的冗余覆盖.最后,通过实例来分析其合理有效性.This paper proposes the information granularity and information entropy of fuzzyβ-neighborhood grain structure,and discusses their application in fuzzyβ-covering decision system.Firstly,the conditional entropy measure in the concept of information measure is introduced into fuzzyβ-covering to describe the uncertainty of fuzzy Vcovering decision system.Secondly,a backward search algorithm is proposed to find the reduction of fuzzyβ-covering family,so that it can delete the redundant covering in the fuzzyβ-covering decision table.Finally,the reasonable effectiveness of this algorithm is analyzed through an example.

关 键 词：模糊β覆盖 模糊β邻域 模糊条件熵 覆盖约简 

分 类 号：O159[理学—数学]