运用粗集理论对逻辑函数进行知识表达的方法，提出了基于粗糙集的组合逻辑优化方法，并给出了相应的算法。
Rough set-based method of combinatory logic optimization was presented by using knowledge expression of logic function with rough set theory, and its corresponding algorithm was given, also.
基于容差关系粗糙集的提出扩大了粗集的应用范围。
The presentation of rough sets based on tolerance relations expands the application scope of rough set theory.
通过粗隶属函数，将粗糙集理论与模糊集理论联系起来，建立一种粗糙集理论与模糊集理论间的关系。
We combine the fuzzy set theory with rough set theory by rough membership function and establish a relation between them.
属性约简是粗糙集理论的一个核心问题，近年来已经成为粗集研究的热点。
Attribute reduction is one of the core issues of the rough set theory and it has become a hot topic of the rough set theory research.
作者从基于分辨矩阵的粗糙集属性约简中受到启发，提出了一系列基于粗集理论的文本特征选择算法，即DB1、DB2、LDB。
The author gains insights from attribute reduction based on discernability matrix and proposes a few rough-set based text feature selection algorithms, i. e. , DB1, DB2 and LDB.
作者从基于分辨矩阵的粗糙集属性约简中受到启发，提出了一系列基于粗集理论的文本特征选择算法，即DB1、DB2、LDB。
The author gains insights from attribute reduction based on discernability matrix and proposes a few rough-set based text feature selection algorithms, i. e. , DB1, DB2 and LDB.
应用推荐