一种基于关系矩阵的决策表正域约简算法  

Reduction Algorithm of Positive Domain for Decision Table Based on Relationship Matrix

作　　者：景运革[1,2] 李天瑞[1] 

机构地区：[1]山西运城学院公共计算机教学部,运城044000 [2]西南交通大学信息科学与技术学院,成都610031

出　　处：《计算机科学》2013年第11期261-264,286,共5页Computer Science

基　　金：国家自然科学基金项目(60873108)资助

摘　　要：研究了粗糙集属性约简问题,引入等价关系矩阵的诱导矩阵和矩阵的λ-截矩阵等概念来计算决策表的上、下近似集,进而给出基于关系矩阵的决策表正域求解方法,并从理论上证明了该方法的正确性。提出了粗糙集属性核的启发式约简,并用该方法计算最小约简,在属性动态增加时,用矩阵快速更新的方法来改变属性等价关系矩阵,可以快速地计算属性变化后的正域。最后,通过实例分析说明了属性约简的具体操作方法和算法的有效可行性。This paper discussed the problem of attributes reduction in rough set. We first introduced both induced ma- trix and λ-cut matrix of equivalence relation matrix to calculate upper and lower approximation of decision tables and then proposed a reduction algorithm of positive domain for decision table based on relationship matrix with the prove of correctness in theory. What＇ s more, a heuristic reduction of attribute core in rough set was proposed to calculate the minimum reduction. With dynamical updating of attributes, we updated attribute equivalence relationship matrix through the method of update of matrix and calculated the positive domain after update of attribute rapidly. The example con- firms the feasibility and effectiveness of proposed operation and method of attribute reduction.

关 键 词：粗糙集 决策表 正域约简 关系矩阵 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]