摘要
粗糙集理论提供了一种有效处理不完整、不确定信息的数学工具。近年来,它被广泛应用于决策分析、数据挖掘、模式识别、智能控制等领域,介绍了粗糙集的基本理论以及其扩展模型,其中详细介绍了变精度、容差、优势、模糊等粗糙集模型。在应用研究方面,主要介绍了粗糙集在特征选择、模式分类两个方面研究进展。
Rough set theory provides a useful mathematical foundation for effectively handling imperfect and uncertain information. Re- cently, the theory and its extensions have been widely applied to many problems, including decision analysis, data mining, pattern rec- ognition and intelligent control. This paper presents an outline of the basic concepts of rough sets and their major extensions, covering variable precision, tolerance, dominance-based and fuzzy rough sets. The successful applications of fuzzy set theory in feature selection and classification are also introduced.
出处
《控制工程》
CSCD
北大核心
2013年第1期1-8,共8页
Control Engineering of China
基金
国家自然科学基金(61074176)
国家自然科学基金(61104214)
国家自然科学基金创新群体(60921003)
关键词
粗糙集
特征选择
规则提取
分类
rough set
feature selection
rule induction
classification
