摘要
粗糙集理论是一种新的处理模糊和不确定性知识的数学工具.相似度是用于比较2个相似的模糊粗糙集所包含信息的精确性大小的,是模糊集理论和粗糙集理论的热点问题之一.文章利用一种改进的相似度定义了模糊粗糙近似算子,重新定义了粗糙集的一些概念,给出并证明了模糊粗糙近似算子的几个性质.
Rough set theory is emerging as a powerful tool for dealing with vagueness and uncertainty problems. Similarity measure between two fuzzy sets can give more accurate information about these, it is one of hot topics in fuzzy set theory and rough set theory. This paper mainly introduces an improved similarity measure into rough set theory, gives the concept of fuzzy rough approximation operators, and further discusses some properties of these operators.
出处
《河北大学学报（自然科学版）》
CAS
北大核心
2008年第1期92-95,共4页
Journal of Hebei University(Natural Science Edition)
基金
国家自然科学基金资助项目(6077306260772073)
河北省科学技术研究与发展课题(0321350106213598)
河北省教育厅资助课题(20062014)
河北大学重点资助课题(2003Z12)
关键词
粗糙集
相似度
模糊粗糙近似算子
rough set
similarity measure
fuzzy rough approximation operators
