多粒度粗糙集模型中属性子集序列的构造方法

doi:10.11772/j.issn.1001-9081.2016.11.2950

计算机应用 ›› 2016, Vol. 36 ›› Issue (11): 2950-2953.DOI: 10.11772/j.issn.1001-9081.2016.11.2950

• 第十六届中国粗糙集与软计算联合学术会议(CRSSC 2016)论文 • 上一篇下一篇

多粒度粗糙集模型中属性子集序列的构造方法

姚晟^1,2, 徐风^1,2, 汪杰^1,2

1. 安徽大学计算机科学与技术学院, 合肥 230601;
2. 计算智能与信号处理教育部重点实验室(安徽大学), 合肥 230601

收稿日期:2016-04-07 修回日期:2016-06-02 出版日期:2016-11-10 发布日期:2016-11-12
通讯作者: 徐风
作者简介:姚晟(1979-),女,安徽合肥人,讲师,博士,主要研究方向:粗糙集、粒计算、大数据;徐风(1993-),男,安徽六安人,硕士研究生,主要研究方向:粗糙集;汪杰(1993-),男,安徽六安人,硕士研究生,主要研究方向:粗糙集。
基金资助:
国家自然科学基金资助项目（61300057，61602004）；安徽省自然科学基金资助项目（1508085MF127，1408085QF120）；安徽大学信息保障技术协同创新中心公开招标课题（ADXXBZ2014-5，ADXXBZ2014-6）；安徽省高等学校自然科学研究重点项目（KJ2016A041）；安徽大学博士科研启动基金资助项目（J10113190072）；安徽大学计算智能与信号处理教育部重点实验室课题项目。

Constructing method of attribute subset sequence in multi-granulation rough set model

YAO Sheng^1,2, XU Feng^1,2, WANG Jie^1,2

1. College of Computer Science and Technology, Anhui University, Hefei Anhui 230601, China;
2. Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education(Anhui University), Hefei Anhui 230601, China

Received:2016-04-07 Revised:2016-06-02 Online:2016-11-10 Published:2016-11-12
Supported by:
This work is partially supported by the National Natual Science Foundation of China (61370050, 61572036), the Natual Science Foundation of Anhui Province (1508085QF134), the Innovation Foundation of Anhui Normal University (2016XJJ074).

摘要/Abstract

摘要： 针对多粒度粗糙集模型中属性子集序列的构造问题，提出一种基于属性间距离的构造方法。该方法首先引入信息系统中属性间距离的概念，并给出距离的定量计算公式；然后根据公式来计算出各个属性之间的距离；最后根据属性之间距离的远近，得到每个属性的邻域属性集，从而构造出一个属性子集序列。实验结果表明，与随机构造的属性子集序列相比，该方法构造的序列对于实验的每个对象类具有更高的近似精度。

关键词: 多粒度, 属性子集序列, 距离函数, 近似精度

Abstract: Concerning the construction problem of attribute subset sequence in multi-granulation rough set model, a construction method based on the distance between attributes was proposed. Firstly, the concept of the distance between attributes in information system was introduced. Secondly, the quantitative calculation formula was given, which was then used to compute the distance between the attributes. Finally, according to the distance between the attributes, the neighborhood attribute set of each attribute was obtained, and then the attribute subset sequence was constructed. The experimental results show that the proposed method is more accurate for each object class of the experiment than the random constructional attribute subset sequence.

Key words: multi-granulation, attribute subset sequence, distance function, approximation accuracy

中图分类号:

TP18

姚晟, 徐风, 汪杰. 多粒度粗糙集模型中属性子集序列的构造方法[J]. 计算机应用, 2016, 36(11): 2950-2953.

YAO Sheng, XU Feng, WANG Jie. Constructing method of attribute subset sequence in multi-granulation rough set model[J]. Journal of Computer Applications, 2016, 36(11): 2950-2953.

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多粒度粗糙集模型中属性子集序列的构造方法

Constructing method of attribute subset sequence in multi-granulation rough set model

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