基于依赖空间的变精度粗糙集属性约简  

Attribute Reduction in Variable Precision Rough Set Based on Dependence Space

作　　者：余承依[1] 李进金[1] 

机构地区：[1]闽南师范大学数学与统计学院,漳州363000

出　　处：《模式识别与人工智能》2014年第12期1065-1070,共6页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.61379021;61303131);福建省教育厅科技项目(No.JA12223)资助

摘　　要：针对求解变精度粗糙集模型属性约简问题,在对象集上定义一种上下近似二元关系.利用此关系建立属性集上的等价关系,由此构造出依赖空间,从而得到变精度粗糙集的上下近似协调集的判定定理.同时建立一种保持每个决策类的上下近似不变的属性约简方法.最后通过实例验证方法的有效性.To get the attribute reduction in variable precision rough set model, an upper and lower approximation binary relation is defined on object sets. By applying the binary relation, the equivalence relation is constructed on attribute sets and thus a dependence space is produced. Then, theorems for judging upper and lower approximation consistent sets are obtained. Meanwhile, a new attribute reduction method is proposed to preserve some invariant characters of upper and lower approximation in each decision class. Finally, a practical example illustrates the validity of the proposed method.

关 键 词：变精度粗糙集 属性约简 二元关系 依赖空间 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]