1) Approximation of class unions
类合集近似
1.
Approximation of class unions is a very important approach in DRSA.
DRSA(Dominance-basedRoughSetApproach)是经典粗糙集理论在支配关系下的扩展,而类合集近似是DRSA中非常重要的概念与方法。
3) approximate set
近似集合
1.
Animage is known as a knowledge system and approximate set of Rough sets theory is applied to detectingedges in images.
每一幅图象表达的信息作为一个知识系统,利用粗糙集中的近似集合概念提取图象的边缘。
4) Set approximate neighbourhood
集合近似邻域
5) graded approximate sets
程度近似集合
6) lower approximation
下近似集
1.
similarity measure, distance measure and entropy measure are defined for the object rank, then upper and lower approximations of concept are defined by using this fuzzy set method , and decision rules are achieved.
本文提出FPS模型解决这种不确定性,并在此基础上,为概念归纳推理定义了模糊粗糙集,为对象的排序定义了相似性测度、距离测度和熵测度,用模糊集方法定义了概念的上下近似集,并得出了决策规则。
补充资料：云合雾集
1.比喻聚集迅速。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条