基于覆盖的粗糙模糊集的粗糙熵

Rough Entropy of Rough Fuzzy Sets Based on Covering

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.