基于代数观点的邻域区间集粗糙集模型研究

Research on the Neighborhood Interval-set Rough Set Model Based on Algebraic Viewpoints

描述部分已知概念的区间集粗糙集是对经典粗糙集的拓展,其属性值概念由上下边界集来描述,具有较好的不确定性刻画能力,能够有效促进数据挖掘、信息度量和知识发现等实际应用。现有研究主要针对离散型数据对象,不能很好地处理现实世界中大量存在的连续型数据对象,因此区间集粗糙集具有改进的空间。该文引入邻域关系,通过Hausdorff距离函数定义区间集邻域粒子,由此构造邻域区间集粗糙集模型,并从代数观点研究其相关概念及性质,最后用实例分析验证其有效性。

The interval-set rough set which describes some known concepts is an extension of the classical rough set,and its attribute value concept is described by upper and lower boundary sets,which has good uncertainty description ability and can effectively promote the practical applications of data mining,information measurement and knowledge discovery.The existing research mainly focuses on discrete data objects,and it can not deal with a large number of continuous data objects in the real world,so the interval-set rough set has room for improvement.In this paper,neighborhood relation is introduced,the neighborhood particles of the interval set are defined by the Hausdorff distance function,the neighborhood interval-set rough set model of is constructed,its related concepts and properties are studied from algebraic viewpoints,and finally its effectiveness is verified by case analysis.