【摘要】 粗糙分析方法是从粗糙集理论发展出来的技术之一 .传统的粗糙分析方法能够从决策表中获取经过属性约简和值约简的决策规则 .这些规则虽然能够提供一定程度的决策支持 ,但是这些规则仅保留了决策表的部分决策支持能力 ,在实际的决策过程中 ,往往无法提供良好的决策支持 .对此 ,该文提出一组用于决策支持的粗糙分析方法 ,称为粗糙决策支持方法 .该方法能够充分挖掘决策表的决策能力 ,以提供强有力的决策支持 ,并且本质上提供容错的决策支持 .该方法与传统方法能够整合为动静结合的决策支持模式 ,并提供强大而又快速的决策支持更多还原

【Abstract】 Traditional rough analysis method can produce a set of reduced decision rules from a decision table by attribute reduction and value reduction. These rules can provide decision support to some extent. However, the process of attribute reduction and value reduction is at the cost of many decision support abilities, so that the obtained rules remain just some part of the whole decision support abilities of the original decision table. In many cases, the set of reduced rules is often unable to offer decision support, which could be offered by the original decision table. A family of rough analysis methods for decision support, called Rough Decision Support Method (RDSM), is proposed in this paper. RDSM can make the best use of the decision support abilities of decision table, and provide powerful decision support. RDSM is essentially an error-tolerable method. RDSM and the traditional method can be combined into a hybrid decision support model, which can offer powerful decision support at high speed.更多还原