摘要
针对信息系统随机模糊属性的约简问题,提出一种新的关于随机模糊属性的知识约简方法。该方法在传统信息系统知识约简基础上,提出了随机模糊信息系统及相关概念,引入了模糊信任测度和似然测度,然后给出并证明了随机模糊信息系统上的知识约简理论。在这些理论的基础上,提出基于模糊信任测度和似然测度的约简方法并分析该算法的时间复杂性。理论分析和例证分析表明,该方法能快速并有效地实现知识约简。
Aiming at the reduction problem of random fuzzy attribute in information system, the article proposes a novel knowledge reduction approach about random fuzzy attribute. On the foundation of traditional information system knowledge reduction, the approach puts forward random fuzzy information system along with its related concepts, introduces fuzzy belief measures and plausibility measures, after that provides and validates the knowledge reduction theory of random fuzzy information system. Based on these theories, the article proposes a reduction approach based on fuzzy belief measures and plausibility measures and analyzes the time complexity of the algorithm. Theoretical analysis and instance analysis elaborate that the approach can quickly and effectively realize knowledge reduction.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第3期242-245,共4页
Computer Applications and Software
基金
国家自然科学基金项目(60603062
61100194)
湖南省重点建设学科
湖南省教育科学十二五规划课题(XJK011BXJ004)
湖南省教育厅科研项目(11C1184)
湖南省科技计划资助项目(2013FJ3032)
湖南省哲学社会科学基金项目(13YBA302)
关键词
信任测度
似然测度
核属性
最小约简
R-蕴含算子
Belief measures Plausibility measures Core attribute Minimal reduction R-implication operator
