摘要
覆盖约简是研究覆盖去冗余问题的一种有效方法。本文在基于最简覆盖的粗糙集模型的基础上,将粗糙度和粗糙熵的概念引入基于最简覆盖的粗糙模糊集,用来度量其不确定性程度;讨论了它们的一些性质,并通过实例说明粗糙熵比粗糙度更能精确地反映基于最简覆盖的粗糙模糊集的不确定性程度。
Covering reduction is an efficient way of research on simplifying covering problem. On the basis of study on generalized rough sets covering reduction, roughness and rough entropy are introduced to discuss the uncertainty of rough fuzzy sets based on covering reduction, and their properties are established. Moreover, we give an example to show that, as an accuracy measure, rough entropy is hotter than roughness.
出处
《计算机科学》
CSCD
北大核心
2006年第10期179-181,共3页
Computer Science
基金
国家自然科学基金项目(60175016
60475019)
山西省高校高科技研究开发项目(20051277)。
关键词
粗糙模糊集
最简覆盖
粗糙度
粗糙熵
Rough fuzzy sets, Covering reduction, Roughness, Rough entropy