基于Rough Set理论的商务决策支持系统知识发现的研究

Knowledge Discovery in Business Decision Support System Based on Rough Set Theory

针对商务决策支持系统中存在信息不确定、冗余数据量大的问题,提出了一种基于Rough Set理论的提取最小规则算法。该算法的核心是改进的分明矩阵属性约简和启发式的属性值约简。通过算法对原始数据表中的冗余属性和属性值进行约简,得到了决策表和最小决策规则。最后,对商务决策支持系统的实例进行数据约简,挖掘其中的隐含知识,获取了有价值的决策信息。

This paper aims to resolve problems of uncertain information and generous data of business information systems based on Rough set theory, and date processing of business information. From the basic concepts of the Rough Set theory, the knowledge expression system of decision- making table is described, and arithmetic of the minimal decision - making regulations is proposed. Finally, the attribute reduction of decision table with the theory is processed and the mining of the hidden knowledge, business decision support system for instance is discussed. The minimal decision - making regulations are deduced.