摘要
模糊粗糙集将模糊集合中的隶属度看作粗糙集理论中的属性值,描述了模糊事件的可能性程度和必然隶属度。详细分析了基于模糊粗糙集的两种属性约简算法FRSAR和CCD-FRSAR,对比了它们的计算复杂性和收敛性,并以计算实例验证了分析结论:CCD-FRSAR总体优于FRSAR。
Fuzzy-rough set treats membership values in fuzzy sets as attribute values in rough set theory, which describes the possible degrees and the certain degrees of fuzzy events. Two attribute reduction algorithms based on fuzzy-rough set, FRSAR and CCD-FRSAR were analyzed and compared in computational complexity and convergency. The conclusion is validated by concrete experiments： as a whole, CCD-FRSAR is better than FRSAR.
出处
《计算机应用》
CSCD
北大核心
2006年第3期635-637,672,共4页
journal of Computer Applications
基金
四川省教育厅重点资助项目(2003A080)
关键词
属性约简
模糊粗糙集
紧计算域
计算复杂性
算法收敛性
attribute reduction
fuzzy-rough set
compact computational domain
computational complexity
convergency
