一种基于知识粒度的决策系统属性约简算法  

Attribute Reduction Algorithm of Decision-Making System Based on Knowledge Granularity

作　　者：廖洪建[1] 

机构地区：[1]柳州师范高等专科学校数学与计算机科学系,广西柳州545004

出　　处：《微电子学与计算机》2013年第2期87-90,共4页Microelectronics & Computer

基　　金：国家自然科学基金项目(60963008)

摘　　要：本文针对决策系统给出了一种新的知识粒度模型,并给出了知识粒度下的核属性定义和分析了知识粒度模型的属性约简与正区域模型的属性约简的等价性.在此基础上利用知识粒度的重要性作为启发式信息构造了决策系统的属性约简算法.算法能够快速获取决策系统的属性约简,算例分析进一步说明了算法的可靠性.In this paper, new measurement method for granularity knowledge model based on decision--making system, and it is proved that attribute reduction based on granularity knowledge model is equivalent to that based on positive region model in decision-- making system, and then attribute reduction algorithm of decision-- making system based on knowledge granularity is proposed, the algorithm quickly calculates attribute reduction in decision-- making system, the example also show that the algorithm is effective and reliable.

关 键 词：知识粒度 决策系统 属性约简 正区域模型 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]