格值信息系统的粗糙熵与不确定度量

Fuzzy Entropy and Uncertain Measurement in Lattice-valued Information Systems

在格值信息系统中引入知识粗糙熵、粗集粗糙熵与不确定度量的概念,得到了相应的重要性质。证明了在格值信息系统中,知识粗糙熵随着知识颗粒变大、分类变粗而单调增大,或者随着知识颗粒变小、分类变细而单调减小。进一步通过讨论它们之间的联系说明了粗集的粗糙熵可以更精确地度量粗集的粗糙程度。这些结论为格值信息系统的知识发现奠定了一定的理论基础。

In the Lattice-valued information system, the concept of knowledge rough entropy, rough set rough entropy and uneertaint measurement is introduced,and the important properties are obtained. In this paper, it is proved that the knowledge rough entropy increases monotonically when the particle of the knowledge increases and the classification of the information system becomes rough. Further, by discussing the relation between them, the rough entropy of rough sets can be more accurate to measure the degree of rough sets. These conclusions lay a theoretical foundation for the knowledge discovery of Lattice valued information systems.