广义模糊粗糙集的包含度和相似度

Inclusion and Similarity Degree of the Generalized Fuzzy Rough Sets

模糊粗糙集是目前数据挖掘领域关注的热点之一,作者在Pawlak粗糙集模型基础上,把一个论域推广为两个论域;把等价关系推广为模糊关系,被近似对象换成模糊集,得到广义模糊粗糙集模型,建立了广义模糊近似空间。在广义模糊近似空间中定义了广义模糊粗糙集上的包含度和相似度,并讨论了此包含度和相似度相关性质。

Fuzzy rough set is the hot point of data mining ifeld nowadays. The paper obtains generalized fuzzy rough set model by expanding one domain to two domains, equation relation to fuzzy relation, approximate object to fuzzy set, sets up generalized fuzzy approximate space, deifnes inclusion and similarity degree and discusses their related properties.