摘要
Pawlak.Z的粗糙集理论与区间值模糊集相结合可以得到区间值模糊信息系统。本文在已有的区间值模糊信息系统概念的基础上,根据模糊等价关系引入了模糊近似空间。从而给出了相似度,进而利用模糊近似空间中任意两个对象集的相似度,定义了区间值模糊信息系统的粗糙隶属度并讨论研究了粗糙隶属度的相关性质。最后,实例验证了这些性质的可行性和有效性。
Rough set theory of Pawlak. Z and interval valued fuzzy sets can be combined. On the basis of the existing concepts of interval valued fuzzy information systems the fuzzy approximation space is introduced according to the fuzzy equivalence relation. Moreover the similarity measure is given and the rough membership measure in interval valued fuzzy information system is defined by the similarity measure of any two objects in the fuzzy approximation space. Then the properties of rough membership measure are discussed in the paper. Finally an example is given to illustrate the feasibility and effectiveness of these properties.
出处
《数码设计》
2017年第6期8-11,共4页
Peak Data Science
基金
国家自然科学基金(NO.61472463
NO.61402064)
重庆市自然科学基金(No.cstc 2015jcyj A40053)
重庆市研究生科研创新基金(NO.CYS16217
NO.CYS17281)
重庆理工大学研究生创新基金(NO.YCX2015227
No.YCX2016227)资助
关键词
粗糙集
区间值模糊信息系统
模糊等价关系
粗糙隶属度
Rough set theory
Interval value fuzzy information system
Fuzzy equivalence relation
Rough membership measure
