粗糙集在销售决策系统中的应用

摘要

There is lots of sales information and uncertain factors in DSS of sales , so it is difficult to make a scientific and rational decision. Rough Set theory is an important tool dealing with uncertainty and incomplete information. Therefore, according to analysing and reasoning Rough Set theory, find useful knowledge in sales information. Present a method that forms the reduction of decision representation using Rough Set. In this paper, use Rough Set theory to deal with useful rules which extract from a large amounts of sales information , analyzing and deducing in order to get the minimal no redundant subsets of attributes and minimized rules. Through the result analysis of a case, the experiment results verify the feasibility of the Rough Set theory and DSS combining method. This combining method is an effective solution for getting and understanding of decision rules for sale IDSS.%在销售决策支持系统中,存在着大量的信息和很多不确定的因素,这使得做出科学合理的决策变得很困难.粗糙集理论是处理不确定性知识与不完整数据的有效工具,因此可以根据粗糙集理论通过分析推理找出销售数据中存在的有用的知识.依据粗糙集理论实现了一种对销售决策表知识简化的方法,采用粗集理论处理大量销售信息,从中提取有用规则,通过分析和推理产生最小决策规则.通过实例分析,验证了粗糙集理论与销售决策支持系统相结合方法的可行性.该方法有效地解决了智能销售决策支持系统中决策规则的获取与理解等问题.