摘要
直觉模糊集同时考虑了对象的隶属度、非隶属度和犹豫度,而散度则能够表示信息之间的差异程度.定义了一种基于χ^2分布的直觉模糊散度测度并讨论了其性质,结果可直接应用在多属性决策和推荐系统中.最后,通过算例验证了该方法的有效性和可操作性.
Since intuitionistic fuzzy sets could provide the information of the membership degree and the non-membership degree,as a generalization of the fuzzy sets it has more expression and flexibility better than the classical fuzzy sets in processing uncertain information data and problems.The divergence measure as a useful tool to measure the differences between information has been widely used in classification problems.An intuitionistic fuzzy divergence measure based on χ^2 distribution is defined and its properties are discussed,these conclusions can be directly applied to multi-attribute decision making and recommendation systems.Finally,an example is given to illustrate its validity and operability.
作者
巩增泰
曹玉斌
GONG Zeng-tai;CAO Yu-bin(College of Mathematics and Statistics,Northwest Normal University,Lanzhou 730070,Gansu,China)
出处
《西北师范大学学报（自然科学版）》
CAS
北大核心
2020年第1期10-20,共11页
Journal of Northwest Normal University(Natural Science)
基金
国家自然科学基金资助项目(61763044)
甘肃省自然科学基金资助项目(18JR3RM238)
关键词
散度测度
Χ^2分布
直觉模糊集
推荐系统
多属性决策
divergence measure
χ^2 distribution
intuitionistic fuzzy set
recommendation system
multi-attribute decision making
