基于粒度矩阵的非协调信息系统知识挖掘

Data Mining of Incompatible Information Systems Based on Granular Matrixes

非协调信息系统的知识挖掘是传统数据挖掘方法实践的难点和最重要的研究方向之一。本文在经典粗糙集理论的基础上进行粒计算结构的设计与相应的计算模型研究,提出了基于上述理论的粒度矩阵非协调信息系统知识挖掘方法。首先定义了保留冗余数据的粒度矩阵、决策规则的协调度算法,以及基于可控协调度的粒度矩阵的可导度计算方法,其次在该研究基础上设计了非协调信息系统的属性约简算法和属性值约简算法。最后的仿真实验和初步的企业应用验证了算法对非协调信息处理的鲁棒性和可用性。本研究为非协调信息系统的知识挖掘提供了一个有效的粒计算模型。

The data mining of incompatible information systems is difficult, and it is one of the most important research directions of classical data mining. This paper studies the structure of granular computing and the model of computation based on the classical rough set and proposes a method for the data mining of incompatible of information systems based on granular matrixes. Firstly, the granular matrix which saves redundant data, the coordination degree algorithm and the con trolled conductivity of granular matrixes are defined. Secondly, the altribute reduction algorithm of incompatible information systems is designed on the basis of the above theory. The final simulation experiments and preliminary enterprise application show the robustness and availability of the algorithm. This study provides an effective granular computation model for the data mining of incompatible information systems.