粒计算中基于属性分类的形式概念属性约简

针对目前已有的形式概念属性约简算法的不足(如属性约简的时间复杂度偏高、属性及属性值比较过程中存在冗余计算、存储开销大等问题),结合粒计算思想,提出基于属性分类的形式概念属性约简模型.首先,通过定义两个算子来划分属性之间分类关系;然后,由属性分类关系制定约简规则,并在此基础上提出基于属性分类的形式概念约简算法,该算法在保持目前最低时间复杂度不变的情况下,减少了冗余计算和存储开销,提高了属性约简的计算效率;最后,通过实例和仿真实验对基于属性分类关系的形式概念属性约简算法的有效性进行了验证.

Formal concept attribute reduction model based on attribute classification relation

In view of the shortcomings of existing formal concept attribute reduction algorithms, such as the problems that the time complexity of attribute reduction is too high, redundancy calculation exists in attribute and attribute value comparison, and storage overhead is great and so on, by combining the idea of granular computing this paper proposes a conceptual attribute reduction model based on attribute classification. Firstly, two operators are defined to classify the relations among attributes. Then, a reduction rule is established by attribute classification relation. On this basis, this paper proposes a formal concept reduction algorithm based on attribute classification, which reduces the redundancy calculation and storage overhead while keeping the current minimum time complexity constant, which improves the computational efficiency of attribute reduction. Finally, the validity of the formal attribute reduction algorithm based on classification is verified by examples and simulation experiments.