基于粗糙集的决策树在产品缺陷检测中的应用

The Application of Decision Tree Technology Based on Rough Sets in Detection of the Plywood Defect

将数据挖掘中的决策树与粗糙集理论进行了有机结合,提出了一种基于粗糙集技术的决策树构造算法,并将该算法应用于胶合板缺陷检测.通过粗糙集属性约简,找出造成胶合板缺陷的关键因素;再基于约简后的决策表,使用该决策树算法构建决策树,从而提取分类规则,指导决策过程.通过实验验证了,该算法可以有效对胶合板的缺陷进行检测.

Through the combination of the Decision Tree and Rough Set Theory in Data Mining, a decision tree construction algorithm based on Rough Set technology is proposed. And the algorithm is applied to the detection of the plywood defect. Rough set attribute reduction is used to find out the key factors caused the plywood defect. Then on the foundation of the reduc- tion decision table, the decision tree is constructed by use of this algorithm, so as to extract the classification rules and to guide the decision-making process. In the end, the experiments prove that the algorithm can detect the plywood defect effectively.