基于直觉模糊粗糙集的属性约简研究  

An Attribute Reduction Algorithm for Intuitionistic Fuzzy Rough Sets

作　　者：樊雷[1] 雷英杰[1] 

机构地区：[1]空军工程大学导弹工程学院,陕西三原713800

出　　处：《计算机工程与科学》2008年第7期79-81,113,共4页Computer Engineering & Science

基　　金：国家自然科学基金资助项目(60773209);陕西省自然科学基金资助项目(2006F18)

摘　　要：本文针对传统的离散化技术所造成的信息丢失问题,提出了利用直觉模糊粗糙集合理论来进行属性约简的方法。文中描述了直觉模糊等价关系下粗糙集的模型,并在此基础之上定义了正域、依赖度与非依赖度概念,然后详细分析了直觉模糊粗糙集属性约简算法。最后,用实例证明了该算法的可行性,并对算法的优缺点进行了阐述。The technology of attribute reduction based on the intuitionistic fuzzy rough set theory is described as to the problem of information loss in the process of discretization. A model of rough sets under intuitionistic fuzzy equivalant relations is systematically investigated, and the definitions of positive field, dependence degree and nondependence degree are given. An attribute reduction algorithm based on intuitionistic fuzzy rough sets is particularly analyzed,and the advantages and disadvantages are compared. Experiments show the feasibility of the application of the algorithm.

关 键 词：直觉模糊集 直觉模糊粗糙集 正域 依赖度 非依赖度 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]