摘要
粗糙集理论是用来分析模糊或不确定性数据集的较新的数学工具 ,根据粗集理论的基本概念 ,系统地给出了一套计算方法 ,并根据属性的重要性为求解属性的最小或次小相对约简设计了一种新的启发式算法 ,文章还给出了任意属性集的全部约简个数的最大值 ,为简化求解全部约简过程提供了帮助。
Rough Set Theory is a new mathematical tool for analyzing the vague or uncertain data set. In this paper,a series of computational methods are proposed systematically according to the basic concepts of Rough Set Theory. First,the classification algorithms for single attribute and multi attributes are introduced, then the method of computing dependency is given, and the computational methods of core and importance and the algorithms of relative core and importance are also described.Finally, a new heuristic algorithm of attributes′ relative reduction is presented.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
2002年第2期161-166,共6页
Journal of Hefei University of Technology：Natural Science
基金
国家自然科学基金资助项目 (79970 0 5 8)
安徽省自然科学基金资助项目 (990 43 64 5 )
