粗糙集理论在装配知识挖掘中的研究与应用

Research and application of roughness set theory in the excavation of assembly knowledge

分析了数字化环境下装配知识的特点,提出了一种基于粗糙集理论的数据挖掘模型。详细阐述了数据挖掘过程中数据泛化、数据归约、多余属性删除、元组合并、规则生成及知识评价等各个步骤。文中以减速器为例,验证了数据挖掘模型的有效性。

Characteristics of assembly knowledge under the digitized environment has been analyzed, a kind of data excavation model based on roughness set theory was put forward. Every step of data generalization, data reduction, deletion of superfluous attributes, combination of tuples, generation of rides and evaluation of knowledge etc. during the course of data excavation were expounded in detail. And taking the speed reducer as an example the effectiveness of data excavation model was verified.