《计算机应用研究》|Application Research of Computers

不完备邻域决策粗糙集的最小化代价属性约简算法

Minimum cost attribute reduction algorithms for incomplete neighborhood decision-theoretic rough set

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作者 姚晟,李初宴,吴照玉
机构 安徽大学 a.计算机科学与技术学院;b.计算智能与信号处理教育部重点实验室,合肥 230601
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文章编号 1001-3695(2021)01-013-0065-04
DOI 10.19734/j.issn.1001-3695.2019.09.0587
摘要 目前的决策粗糙集研究主要集中在完备离散型信息系统,很少有对不完备连续型数据进行研究,考虑这一问题,提出一种不完备邻域决策粗糙集模型。首先在不完备连续型数据中引入了不完备邻域关系,然后利用该二元关系对传统的决策粗糙集进行重构,一种称之为不完备邻域决策粗糙集的模型被提出,同时基于决策代价原则,进一步地提出了最小化决策代价的属性约简算法。最后通过实验表明了所提出的算法具有更高的属性约简性能。
关键词 粗糙集; 不完备邻域关系; 最小决策代价; 属性约简
基金项目 国家自然科学基金资助项目(61602004,61300057)
安徽省自然科学基金资助项目(1508085MF127)
安徽省高等学校自然科学研究重点资助项目(KJ2016A041)
安徽大学信息保障技术协同创新中心公开招标课题资助项目(ADXXBZ20145,ADXXBZ20146)
安徽大学博士科研启动基金资助项目(J10113190072)
本文URL http://www.arocmag.com/article/01-2021-01-013.html
英文标题 Minimum cost attribute reduction algorithms for incomplete neighborhood decision-theoretic rough set
作者英文名 Yao Sheng, Li Chuyan, Wu Zhaoyu
机构英文名 a.College of Computer Science & Technology,b.Key Laboratory of Intelligent Computing & Signal Processing,Ministry of Education,Anhui University,Hefei 230601,China
英文摘要 The current research on decision-theoretic rough sets mainly focuses on the complete discrete information system, and few studies on incomplete continuous data. Considering this problem, this paper proposed an incomplete neighborhood decision-theoretic rough set model. Firstly, it introduced incomplete neighborhood relation into incomplete continuous data, and then reconstructed the traditional decision-theoretic rough sets by the binary relation, proposed a model called incomplete neighborhood decision-theoretic rough sets. At the same time, based on the principle of decision cost, it proposed an attribute reduction algorithm to minimize the decision cost. Finally, experiments show that the proposed algorithm has better performance in attribute reduction.
英文关键词 rough set; incomplete neighborhood relations; minimum decision cost; attribute reduction
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收稿日期 2019/9/11
修回日期 2019/10/25
页码 65-68
中图分类号 TP18
文献标志码 A