不完备信息系统中基于集对相似度的粗集模型  

Extension of Rough Set Model Based on SPA Similarity Degree in Incomplete Information Systems

作　　者：陈圣兵[1] 李龙澍[1,2] 纪霞[1] 卞世晖[1] 

机构地区：[1]安徽大学计算智能与信号处理教育部重点实验室,合肥230039 [2]安徽大学计算机科学与技术学院,合肥230039

出　　处：《计算机科学》2010年第7期186-190,共5页Computer Science

基　　金：国家自然科学基金(60273043);安徽省自然科学基金项目(090412054)资助

摘　　要：讨论了已有粗集扩充模型处理不完备信息的局限,分析了空值相等与确定值相等在概率上的明显差异。依据集对分析理论,提出了集对相似度和相似度容差关系,进而给出一种基于集对相似度的粗集拓展模型。该模型的方法是:通过引入差异度系数体现空值相等与确定值相等之间的差别,利用相似度容差关系及差异度系数确定数据对象的邻域,再利用该邻域得到上下近似集,同时在求上近似时忽略空值的差异性,在求下近似时强调空值的差异性。实验表明,该模型在相同阈值参数的情况下,结果更加合理,精度更高。In view of the limitations of existing extension of rough set models for processing incomplete information,the difference between null value＇s equality and known value＇s equality was analysed on probability. Based on the theory of Set Pair Analysis, SPA Similarity Degree and Similarity Tolerance Relation were proposed, and the method of extension of rough set model based on SPA Similarity Degree was described also. It discriminates null value＇s equality from known value＇s equality by using the coefficient of difference degree, and gets the neighborhood of object according to coefficient of difference degree and similarity tolerance relation, than gets upper approximation and lower approximation according to the neighborhood. The difference of null value ＇s equality is ignored when we compute upper approximation, and the difference of null value＇s equality is emphasized for lower approximation. The results of the experiment reveal that both the classification capability and the precision of rough set are better than other models.

关 键 词：粗集 空值 等价关系 集对分析 不完备信息系统 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]