摘要
直觉模糊粗糙集和多粒度粗糙集都是近几年来研究的热门课题.首先通过定义Pawlak近似空间中的支撑函数给出了一般多粒度直觉模糊粗糙近似算子的定义,并讨论了一般多粒度直觉模糊粗糙上、下近似算子的性质.其次,研究了一般多粒度直觉模糊粗糙集(λ1,λ2)截集的定义和性质.此外,还研究了一般多粒度直觉模糊集的不确定性度量以及参数(λ1,λ2)的一般多粒度直觉模糊粗糙集的不确定性度量.最后通过淘宝信息反馈的例子验证了模型的实用性和有效性.
The researches of intuitionistic fuzzy rough set and multi-granulation rough set are important in recent years.In this paper,the definitions and properties of general multi-granulation intuitionistic fuzzy rough approximation operators have been studied by supporting function in Pawlak approximation space.Secondly,the properties and definitions of（λ1,λ2）cut sets of general multi-granulation intuitionistic fuzzy rough set have been discussed too.What＇s more,the measures of general multi-granulation intuitionistic fuzzy rough set and（λ1,λ2）general multi-granulation intuitionistic fuzzy rough set have also been studied.Finally,an example about taobao information feedback illustrates feasibility and efficiency of this model.
出处
《西南师范大学学报（自然科学版）》
CAS
北大核心
2017年第6期8-18,共11页
Journal of Southwest China Normal University(Natural Science Edition)
关键词
直觉模糊集
粗糙集
多粒度
不确定性度量
intuitionistic fuzzy set
rough set
multi-granulation
measure
