基于辨识矩阵的直觉模糊决策系统属性约简算法

Attribute Reduction in Intuitionistic Fuzzy Decision Systems Based on Discernibility Matrix

基于粗糙集和直觉模糊集理论,提出了研究直觉模糊决策系统的属性约简算法。通过引入基于加权的欧氏距离的相似度和相异度,构造α, β-相似关系,导出α, β-极大一致块,进而构造出直觉模糊决策系统的辨识矩阵,得到基于辨识矩阵的属性约简算法。实例验证表明,该算法在数据存在一定误差的情况下也能得到很好的效果。

Based on the theory of rough sets and intuitionistic fuzzy sets,attribute reduction in intuitionistic fuzzy decision systems(IFDS)is proposed.Firstly,an intuitionistic fuzzy rough set model based on the similarity relation is established.Secondly,the discernibility matrix based on the maximal consistent block is constructed and an algorithm of attribute reduction is designed,which can eliminate the redundant information from the given IFDS.Finally,an illustrative example is employed to verify the reasonability and effectiveness of the algorithm in this paper,and it shows that the algorithm can get good results even if there are some errors in the data.