协调的不完备多粒度标记决策系统的最优粒度选择

摘要

针对具有多粒度标记的不完备信息系统的知识获取问题展开研究，首先，介绍不完备多粒度标记信息系统的概念，在不完备多粒度标记信息系统中的对象集上定义相似关系。然后，给出在不同粒度层面下信息粒度的表示及其相互关系，并进一步定义基于相似关系的集合的下、上近似概念，讨论它们的性质。最后，用证据理论中的信任函数和似然函数刻画协调的不完备多粒度标记决策系统的最优粒度选择特征。%Aiming at knowledge acquisition in incomplete information systems with multi-granular labels, the concept of incomplete multi-granular labeled information systems is firstly introduced. Similarity relations of an incomplete multi-granular labeled information system are then defined. Representations of information granules with different levels of granulation as well as their relationships are also explored. Lower and upper approximations based on similarity relations with different levels of granulation are further defined and their properties are presented. Finally, by belief and plausibility functions in Dempster-Shafer theory of evidence, optimal granularity selections in consistent incomplete multi-granular labeled decision systems are discussed.