基于条件粗糙熵的粗集不确定性度量  

Uncertainty measurement of rough sets based on conditional entropy

作　　者：李健[1] 史开泉[1] 

机构地区：[1]山东大学数学与系统科学学院,山东济南250100

出　　处：《系统工程与电子技术》2008年第3期473-476,共4页Systems Engineering and Electronics

基　　金：福建省自然科学基金资助课题(JA04268)

摘　　要：基于知识的条件粗糙熵理论,提出了集合的条件粗糙熵(简称条件熵)概念,用来刻画和度量集合的不确定性(粗糙性)。给出集合条件熵的性质和相关定理:在近似空间中,等价划分越细,集合的条件熵就越小,粗糙性也就越小;不同的决策集合并后粗糙性会降低.讨论了集合的条件熵在目标信息系统中的理论意义,集合的条件熵刻画了目标信息系统的局部(某个决策集)的不确定性。Based on the conditional rough entropy theory, the definition of the conditional rough entropy of set is given and it can measure the uncertainty of set. The properties and the related theorems are given. In approximate space the thinner the equivalence partition is, the smaller the conditional entropy of set is and the smaller the roughness is. Uniting the different sets makes the roughness lower. The theory significance of condi- tional rough entropy in decision information system is discussed. The conditional rough entropy measures the partial uncertainty in decision information systems.

关 键 词：条件粗糙熵 不确定性 粗糙性 目标信息系统 

分 类 号：O159[理学—数学]