不完备信息系统中一种新的不确定性度量方法

A New Uncertainty Measurement Method in Incomplete Information System

不确定性度量是智能计算等领域中一个重要的研究问题。在不完备信息系统中,为了融合众多不确定性度量方法的优点,引入近似粗糙度度量方法,由于该度量方法存在一定的缺陷,接着在近似粗糙度中融合知识粒度度量,提出一种新的不确定性度量方法,同时在所提出度量方法的基础上加入了一个平滑因子,以提高该度量方法在不确定性度量时的适用性。实验结果表明所提出的方法具有更好的不确定性度量效果。

Uncertainty measurement is an important research issue in alias such as intelligent computing. In in- complete information system, in order to fuse the advantages of many uncertainty measurement methods, the ap- proximation roughness is firstly introduced. Because the measurement method exists certain defects, then the measurement of knowledge granularity is fused in approximation roughness, and a new uncertainty measurement method is proposed. Meanwhile, a smoothing factor is added to the proposed measurement method to improve its applicability in the uncertainty measurement. Finally, the experimental results show that the proposed method has a better effect on the uncertainty measurement.