基于矩阵的混合型邻域决策粗糙集增量式更新算法

决策粗糙集模型是当前粗糙集理论最为重要的研究分支之一.然而,由于现实环境下数据类型的复杂多样以及数据的动态更新,使得传统的决策粗糙集模型面临着一定的局限和不足,针对这一问题,提出一种混合型信息系统的邻域决策粗糙集模型,并设计出一种矩阵方法的邻域决策粗糙集增量式更新算法.首先,将传统的离散型决策粗糙集模型在混合型信息系统...

Incremental updating algorithms of neighborhood decision-theoretic rough set model for hybrid data based on matrix

Decision-theoretic rough set model is one of the most important research branches of the rough set theory. However, due to the variety of data types and the dynamic updating of data in the real environment, the traditional decision-theoretic rough set model is faced with certain limitations and deficiencies. To solve this problem, a neighborhood decision-theoretic rough set model of a hybrid information system is proposed, and an incremental updating algorithm of a neighborhood decision-theoretic rough set based on matrix methods is designed. In this paper, the traditional discrete decision-theoretic rough set model is extended to the hybrid information system, and a neighborhood decision-theoretic rough set model is proposed, which can deal with the hybrid data directly. Then, the matrix method is used to represent the neighborhood decision-theoretic rough set model. At the same time, the incremental updating of the neighborhood decision-theoretic rough set model is studied through the matrix in the case of the increase and decrease of the objects in the hybrid information system. The efficiency of this incremental method is proved theoretically. Finally, based on the incremental updating method of matrix, the incremental updating algorithm of the neighborhood decision-theoretic rough set for the hybrid information system is proposed. Experimental results show that the proposed incremental updating algorithm has certain effectiveness and superiority.