粗糙集研究综述
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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.Recently,the theory and its extensions have been widely applied to many problems,including decision analysis,data mining,pattern recognition 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.
Rough set theory provides a useful mathematical foundation for effectively handling imperfect and uncertain information.Recently,the theory and its extensions have been widely applied to many problems,including decision analysis,data mining,pattern recognition 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.
引文
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