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多粒度粗糙集模型中属性子集序列的构造方法
引用本文: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.
作者姓名:姚晟  徐风  汪杰
作者单位: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
基金项目: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。
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  
收稿时间:2016-04-07
修稿时间:2016-06-02

Constructing method of attribute subset sequence in multi-granulation rough set model
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.
Authors:YAO Sheng  XU Feng  WANG Jie
Affiliation: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
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.
Keywords:multi-granulation                                                                                                                        attribute subset sequence                                                                                                                        distance function                                                                                                                        approximation accuracy
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