摘要
粗糙集理论是一种新型的处理模糊和不确定知识的数学工具,其对知识的理解是认为知识与分类相关、知识是有粒度的。文中利用粗糙集理论中的二进制可辨矩阵讨论知识的粒度计算及其应用,得到了二进制可辨矩阵若干定理及推论,并提出计算知识的分辨度和属性重要度的新方法,利用这些理论和公式,可快速计算出知识的分辨度和属性重要度,相对正域和负域等,为以后的属性约简和规则提取打下基础。并给出这些方法的应用,表明了文中提出的方法的有效性。
Rough set is a new instrument in math. It considers that knowledge is connected with kinds and knowledge has granulation. This paper introduces calculation and application of knowledge granulation by using binary discemable matrix. Several theorems and deducation of binary discernable matrix are gained by utilizing these concepts. This paper proposes a new computational method of knowledge resolu- tion and the significance of attribute. By utilizing the results gained, they can be calculated quickly, for example：knowledge resolution, the significance of attribute, relation positive regions and relation negative regions, etc. Attribution reduction and rule obtaintion can be based on these theorems, too. The application of the methods in the paper demonstrates the effectiveness of the result obtained.
出处
《计算机技术与发展》
2006年第10期91-93,共3页
Computer Technology and Development
关键词
粗糙集
二进制可辨矩阵
粒度
重要度
rough .set
binary discemable matrix
granulation
significance
