摘要
多粒度粗糙集是粗糙集模型在多粒度及分布式环境中的一种重要拓展形式,而覆盖粗糙直觉模糊集是处理不确定性问题的一种有效方法.为了更有效的处理不确定性问题,将多粒度粗糙集与覆盖粗糙直觉模糊集结合,建立了多粒度覆盖粗糙直觉模糊集模型,并给出了该模型下的一些性质;同时提出了多粒度覆盖粗糙直觉模糊集的模糊度的概念,讨论了其不确定性度量;最后给出了算例.
Exploring rough sets from the perspective of multi-granulation represents a promising direction in rough set theory,where concepts are approximated by multiple granular structures represented by binary relations.While covering rough-intuitionistic fuzzy sets provide an effective method to deal with the uncertainty in data.Through a combination of multi-granulation rough set with covering rough-intuitionistic fuzzy set,we construct a new multi-granulation rough set model,called a multi-granulation covering rough-intuitionistic fuzzy set model,which can be applied to deal with uncertainty more effectively.Then we present some properties,such as monotonicity,duality property and so on,which are similar to those of the classical rough set.We also introduce the concept of fuzziness to describe the uncertainty of this model.Finally,we examine our approach with a detailed example.
出处
《南京大学学报（自然科学版）》
CAS
CSCD
北大核心
2015年第2期438-446,共9页
Journal of Nanjing University（Natural Science）
基金
国家自然科学基金(61379021
11301367
11061004)
福建省自然科学基金(2013J01029)
闽南师范大学研究生科研立项(YJS201410)
关键词
多粒度
覆盖粗糙直觉模糊集
粗糙隶属函数
模糊熵
模糊度
multi-granulation
covering rough-intuitionistic fuzzy set
rough membership function
fuzzy entropy
fuzziness
