计算机科学

计算机科学 ›› 2018, Vol. 45 ›› Issue (7): 178-185.doi: 10.11896／j.issn.1002-137X.2018.07.031

• 人工智能 • 上一篇    下一篇

区间值决策系统的局部属性约简

尹继亮,张楠,赵立威,陈曼如   

  1. 烟台大学数据科学与智能技术山东省高校重点实验室 山东 烟台264005;
    烟台大学计算机与控制工程学院 山东 烟台264005
  • 收稿日期:2018-03-17 出版日期:2018-07-30 发布日期:2018-07-30
  • 作者简介:尹继亮(1994－),男,硕士生,主要研究方向为粗糙集、数据挖掘与机器学习,E-mail:yinjiliangyt@126.com;张 楠(1979－),男,博士,硕士生导师,CCF会员,主要研究方向为粗糙集、认知信息学和人工智能,E-mail:zhangnan0851@163.com(通信作者);赵立威(1996－),男,主要研究方向为粗糙集、数据挖掘,E-mail:zlwazj1996@163.com。
  • 基金资助:
    本文受国家自然科学基金项目(61403329,61572418,61702439,61572419,61502410),山东省自然科学基金项目(ZR2018BA004,ZR2016FM42),烟台大学研究生科技创新基金项目(YDZD1807)资助。

Local Attribute Reduction in Interval-valued Decision Systems

YIN Ji-liang ,ZHANG Nan ,ZHAO Li-wei ,CHEN Man-ru   

  1. Key Lab for Data Science and Intelligence Technology of Shandong Higher Education Institutes, Yantai University,Yantai,Shandong 264005,China;
    School of Computer and Control Engineering,Yantai University,Yantai,Shandong 264005,China
  • Received:2018-03-17 Online:2018-07-30 Published:2018-07-30

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摘要： 区间值决策系统中已有的属性约简工作主要针对决策属性中所有的决策类。针对区间值决策系统中决策属性的某些特定类,引入了区间值决策系统局部约简的概念,提出了部分决策类约简的判定定理;利用差别矩阵方法研究局部约简的结构,并给出了基于差别矩阵的局部约简算法。通过局部约简的概念对区间值决策系统的全局约简结构进行进一步刻画,讨论了不协调区间值决策系统的局部约简和全局约简之间的关系。最后通过相关实验验证了所提算法的可行性和有效性。

关键词: 差别矩阵, 局部约简, 区间值决策系统, 全局约简, 特定类

Abstract: The existing attribute reduction in interval-valued decision system is mainly relative to all decision classes.For some special classes of decision attributes in interval-valued decision system,the concept of local reduction and the judgment theorem of partial decision classes were introduced in this paper.Besides,the structure of local reduction was studied by using the method of discernibility matrix,and the local reduction algorithm based on discernibility matrix was given.The structure of the global reduction in interval-valued decision system was further depicted through the concept of the local reduction,and the relationship between the local reduction and global reduction was discussed.Finally,related experiments were carried out.The experimental results show the feasibility and effectiveness of the proposed algorithm.

Key words: Discernibility matrix, Global reduction, Interval-valued decision system, Local reduction, Specific classes

中图分类号: 

  • TP181
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