摘要
粗糙集和直觉模糊集的融合是一个研究热点。在粗糙集、直觉模糊集和覆盖理论基础上,给出了模糊覆盖粗糙隶属度和非隶属度的定义。考虑到元素自身与最小描述元素的隶属度和非隶属度之间的关系,构建了两种新的模型——覆盖粗糙直觉模糊集和覆盖粗糙区间值直觉模糊集,证明了这两种模型的一些重要性质,与此同时定义了一种新的直觉模糊集的相似性度量公式,并用实例说明其应用。
It is a hot research topic for the combination of rough sets and intuitionistic fuzzy sets.In this paper,the concept of fuzzy covering-based rough membership and non-membership were defined based on the rough sets theory,intuitionistic fuzzy sets theory and covering theory.The relationships between the memberships and non-memberships of the elements themselves and the minimal descriptions of elements were taken into full account.Then two new models were established,which are covering-based rough intuitionistic fuzzy sets model and covering-based rough interval-valued intuitionistic fuzzy sets model.And their properties were proved.At the same time,a new similarity measure formula was proposed in the intuitionistic fuzzy sets,and we used an example to illustrate its application.
出处
《计算机科学》
CSCD
北大核心
2016年第1期44-48,68,共6页
Computer Science
基金
国家自然科学基金计划项目(61273018)
河南省基础与前沿技术研究计划项目(132300410174)
河南省教育厅计划项目(14A520082)
新乡市重点科技攻关计划项目(ZG14020)资助
关键词
直觉模糊集
粗糙集合
模糊覆盖粗糙隶属度
直觉模糊集的相似性度量
Intuitionistic fuzzy sets
Rough sets
Fuzzy covering-based rough membership
Similarity measure formula of the intuitionistic fuzzy sets
