[1]朱晓钟 杨勇 朱英丽.考虑属性排名的约简算法[J].计算机技术与发展,2010,(12):82-85.
　ZHU Xiao-zhong,YANG Yong,ZHU Ying-li.A Reduction Algorithm Considering Ranking Order of Attributes[J].,2010,(12):82-85.
点击复制

考虑属性排名的约简算法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2010年12期
页码:
82-85
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
A Reduction Algorithm Considering Ranking Order of Attributes
文章编号:
1673-629X（2010）12-0082-04
作者:
朱晓钟1; 2 杨勇1 朱英丽1
[1]西北师范大学数学与信息科学学院[2]河海大学计算机与信息学院
Author(s):
ZHU Xiao-zhong; YANG Yong; ZHU Ying-li
[1]College of Mathematics and Information Science,Northwest Normal University[2]College of Computer and Information,Hohai University
关键词:
属性排名; 粗糙集; 属性约简; 二进制区分矩阵
Keywords:
ranking order of attributes;  rough set;  attribute reduction;  binary discernibility matrix
分类号:
TP311
文献标志码:
A
摘要:
属性约简是粗糙集研究的重要内容之一。目前有多种计算约简集的方法,但计算效率普遍不高。杨萍等学者提出的基于二进制区分矩阵的启发式约简算法,考虑了属性的区分度和区分率,采用高效的逻辑运算获得约简集,提高了运算的效率。在该算法的基础上,首先指出其计算所得的约简集存在不确定性,然后给出一种考虑属性排名的改进的约简算法,消除了约简集的不确定性,并且可以迎合用户的需求。最后通过一个信息系统实例,验证该算法的可行性和有效性
Abstract:
The attribute reduction is one of the major contents of rough set research.There are a variety of methods based on rough set theory to compute reduct set of an information system,but their computational efficiency is always not high.Yang Ping proposed a heuristic reduction algorithm based on binary-valued discernibility matrix,taking into account the degree and ratio of differentiation between condition attributes,adopting efficient logical operator computation to obtain reduct set.Based on the thesis of Yang Ping＇s algorithm,first of all points out the result of Yang Ping＇s algorithm is a reduct with some kind of uncertainty,then proposed an improved algorithm considering ranking of condition attributes.It eliminates the uncertainty of final reduct and meets the needs of user simultaneously.Finally,an information system example is used to show its feasibility and effectiveness

相似文献/References:

[1]夏奇思 王汝传.基于属性约简的粗糙集海量数据分割算法研究[J].计算机技术与发展,2010,(04):5.
　XIA Qi-si,WANG Ru-chuan.Mass Data Partition for Rough Set on Attribute Reduction Algorithm[J].,2010,(12):5.
[2]张政超 关欣[] 何友 李应升 郭伟峰.粗糙集理论数据处理方法及其研究[J].计算机技术与发展,2010,(04):12.
　ZHANG Zheng-chao,GUAN Xin[],HE You,et al.Rough Sets Data Processing Method and Its Research[J].,2010,(12):12.
[3]杨乐婵 邓松 徐建辉.基于BP网络的洪灾风险评价算法[J].计算机技术与发展,2010,(04):232.
　YANG Le-chan,DENG Song,XU Jian-hui.Flood Risk Evaluation Algorithm on BP Net[J].,2010,(12):232.
[4]张学友 苗强 毛军军.基于粗糙度的一种分形维数计算方法[J].计算机技术与发展,2010,(05):136.
　ZHANG Xue-you,MIAO Qiang,MAO Jun-jun.A Calculation Method of Fractal Dimension Based on Roughness[J].,2010,(12):136.
[5]李学文 王小刚.优势信息系统的属性约简算法[J].计算机技术与发展,2009,(08):107.
　LI Xue-wen,WANG Xiao-gang.Algorithm on Attribute Reduction in Dominance Information System Based on Dominance Relation[J].,2009,(12):107.
[6]徐沈 吴涛[] 李国成.产业结构调整的量化分析[J].计算机技术与发展,2009,(08):178.
　XU Shen,WU Tao,LI Guo-cheng.Quantitative Analysis on Adjustment of Industrial Structure[J].,2009,(12):178.
[7]申锦标 吕跃进.粗糙集的近似约简及其算法[J].计算机技术与发展,2009,(12):17.
　SHEN Jin-biao,LU Yue-jin.A Rough Set of Approximate Attribute Reduction and Its Algorithm[J].,2009,(12):17.
[8]王小菊 蒋芸 李永华.基于依赖度之差的属性重要性评分[J].计算机技术与发展,2009,(01):67.
　WANG Xiao-ju,JIANG Yun,LI Yong-hua.Significance of Attribute Evaluation Based on Dependable Difference[J].,2009,(12):67.
[9]汪小燕 杨思春.基于改进的二进制可辨矩阵的核增量式更新方法[J].计算机技术与发展,2009,(01):97.
　WANG Xiao-yan,YANG Si-chun.An Incremental Updating Approach to Compute a Core Based on Improved Binary Discernable Matrix[J].,2009,(12):97.
[10]单雪红 吴涛[] 徐文婷[].基于粗糙集的石油安全预警规则提取[J].计算机技术与发展,2009,(01):251.
　SHAN Xue-hong,WU Tao[],XU Wen-ting[].Rules Set of China Oil Security Early Warning Based on Rough Set[J].,2009,(12):251.

备注/Memo

备注/Memo:
国家自然科学基金（10771171）; 兰州市科技计划项目（2008-1-34）朱晓钟（1978-），男，硕士，讲师，CCF会员，研究方向为机糙集理沦及数据挖掘；杨勇，博士，副教授，研究方向为粗糙集理论及其应用
更新日期/Last Update: 1900-01-01