Approaches to attribute reductions based on rough set and matrix computation in inconsistent ordered information systems
Approaches to attribute reductions based on rough set and matrix computation in inconsistent ordered information systems
复制标题
不一致有序信息系统中基于粗糙集和矩阵计算的属性约简方法
DOI：
10.1016/j.knosys.2011.11.013
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发表时间：
2012-03-01
影响因子：
8.8
通讯作者：
Liao, Xiuwu
中科院分区：
文献类型：
--
作者：
Xu, Weihua;Li, Yuan;Liao, Xiuwu
为了在有序的信息系统中进行分类分析，在本文中提出了有关可能和兼容的分布减少的概念。检查了与两个降低相关的判断定理和可见度矩阵，我们可以从中获得对粗糙集理论的两种减少的方法。此外，还考虑了在不一致的有序信息系统中的这两种形式的减少形式的方法中，还考虑了兼容和兼容的决策分配矩阵。构建了矩阵计算的算法，以构建可能和兼容的分布减少，我们可以为这两种形式的分布降低提供另一种有效方法。为了解释和帮助理解该算法，设计了一个实验计算程序，并使用了两个案例作为案例研究。小规模案例的结果是通过可见度矩阵和矩阵计算进行比较的，以验证我们在本文中研究的新方法。大规模案例是通过实验计算程序计算的，并通过减少的定义进行验证。 （c）2011 Elsevier by。版权所有。
In order to conduct classification analysis in inconsistent ordered information systems, notions on possible and compatible distribution reductions are proposed in this paper. The judgement theorems and discernibility matrices associated with the two reductions are examined, from which we can obtain an approach to the two reductions in rough set theory. Furthermore, the dominance matrix, possible and compatible decision distribution matrices are also considered for approach to these two forms of reductions in inconsistent ordered information systems. Algorithms of matrix computation for possible and compatible distribution reductions are constructed, by which we can provide another efficient approach to these two forms of distribution reductions. To interpret and help understand the algorithm, an experimental computing program is designed and two cases are employed as case study. Results of the small-scale case are calculated and compared by the discernibility matrix and the matrix computation to verify the new method we study in this paper. The large-scale case are calculated by the experimental computing program and validated by the definition of the reductions. (C) 2011 Elsevier By. All rights reserved.