摘要： 研究覆盖广义粗糙集中近似集变化的增量更新问题，分析属性增删时覆盖广义粗糙集模型近似集的性质，根据边界域与近似集关系，得出属性集变化时近似集的变化趋势，并在此基础上，提出一种属性集变化时近似集的动态增量更新方法。通过实例验证该方法的有效性。
关键词:
粗糙集,
知识发现,
属性集,
增量更新,
近似集
Abstract: This paper researches the variation of approximate set in covering generalized rough set when the attribute set changes, through analyzing the approximate set properties and discussing the relation between boundary and approximate set when the attribute set varies with time, it concludes the variation trend of the approximate set, on the basis of this, the paper proposes an method for updating approximate set incrementally. Examples show the validity of the proposed method.
Key words:
rough set,
knowledge discovery,
attribute set,
incremental updating,
approximate set
中图分类号:
刘永文, 李天瑞, 陈红梅, 高子喆, 谷小广. 覆盖广义粗糙集中近似集增量更新方法研究[J]. 计算机工程, 2012, 38(2): 156-158.
LIU Yong-Wen, LI Tian-Rui, CHEN Gong-Mei, GAO Zi-Zhe, GU Xiao-An. Research on Approximate Set Incremental Updating Method in Covering Generalized Rough Set[J]. Computer Engineering, 2012, 38(2): 156-158.