基于粒度的知识粗糙性研究

粒度计算是粗糙集理论研究的一种强有力的工具。在粗糙集理论中,提出知识是有粒度的并定义了知识粗糙度的概念。众所周知,知识获取是专家系统开发的"瓶颈"问题。文中主要从知识粒度、分辨度以及重要度等方面入手,着重研究了知识粗糙性的粒度原理与知识粗糙性的关系,提出了一种基于属性重要度的粗糙性知识获取算法,并通过理论与实验,证明该算法是正确的,行之有效的。

On the Roughness of Knowledge Based on Granularity

Granular computing is emerging as a powerful tool for rough set theory.The theory of rough-set points out that knowledge has granularity and defines the concept of roughness of knowledge.It's well known that the difficulties of system-developing lie in the acquisition of knowledge.From the granularity,recognizability and importance of knowledge,studies the relationship between the roughness of knowledge and its priciple of granularity,puts forward a method of acquiring knowledge based on the importance of attributes,and proves the feasibility of this merthod through theory and experiments.