期刊文献+

基于差分演化算法的粗糙集属性约简 被引量:2

Attribute reduction of rough set based on differential evolutionary algorithm
下载PDF
导出
摘要 属性约简是粗糙集(RS)理论的核心内容之一。应用差分演化(DE)算法求解最小属性约简是一个新的方向。对差分演化算法进行了改进,给出了一种新的适应值函数的定义形式;并在此基础上提出了基于差分演化算法的属性约简算法。最后利用多组数据对该算法进行了仿真实验,并与现有算法进行了比较分析。实验结果表明该算法是有效的,能快速地进行属性约简。 The attribute reduction is one of the cores of Rough Set ( RS) theory. To solve minimum attribute reduction by Differential Evolution ( DE) algorithm is a new direction. In this paper, an improved differential evolution algorithm and a new definition form of fitness function were proposed. And on this basis, an attribute reduction algorithm based on the improved differential evolutionary algorithm was put forward. Finally, the simulation experiments and a comparative analysis with an existing algorithm were carried out for the algorithm with multiple sets of data. The experimental results show that the algorithm is effective and fast.
作者 高意 颜宏文
出处 《计算机应用》 CSCD 北大核心 2010年第9期2329-2331,共3页 journal of Computer Applications
基金 湖南省教育厅基金资助项目(09C083)
关键词 粗糙集 属性约简 差分演化算法 种群 Rough Set ( RS) attribute reduction Differential Evolution ( DE) algorithm population
  • 相关文献

参考文献13

二级参考文献67

共引文献393

同被引文献23

  • 1SCHOLKOPF B,MIKA S,BURGESC J C,et al.Input space versusfeature space in kernel-based methods[J].IEEE Tran on NeuralNetworks,1999,10(5):1000-1017. 被引量:1
  • 2GUO Hai-xiang,ZHU Ke-jun,GAO Si-wei,et al.An improved geneticK-means algorithm for optimal clustering[C]//Proc of the 6th IEEEInternational Conference on Data Mining Workshops.Washington DC:IEEE Computer Society,2006:793-797. 被引量:1
  • 3STORN R,PRICE K.Minimizng the real functions of the ICEC'96contest by differential evolution[C]//Proc of IEEE International Con-ference on Evolutionary Computation.Nagoya:IEEE,1996:842-844. 被引量:1
  • 4STORN R,PRICE K.Differential evolution:a simple and efficientadaptive scheme for global optimization over continuous spaces[R].Berkeley:University of California,2006:643-689. 被引量:1
  • 5PEI Zhen-kui,YU Hui,ZHAO Yan-Li.Image restoration based ondifferent evolution algorithm[J].Journal of PLA University of Sci-ence and Technology:Natural Science Edition,2010,11(5):489-492. 被引量:1
  • 6LIU jun-hong,LAMPINEN J.A fuzzy adaptive differential evolutionalgorithm[J].Soft Computing,2005,9(6):448-462. 被引量:1
  • 7Pawlak Z.Rough sets[J].International Journal of Computer and Information Science,1982,11(5):341-356. 被引量:1
  • 8Yao Y Y,Wong S K M,Lingras P.A decision-theoretic rough set model[C]//Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems,1990. 被引量:1
  • 9Yao Y Y,Wong S K M.A decision theoretic framework for approximating concepts[J].International Journal of Manmachine Studies,1992,37(6):793-809. 被引量:1
  • 10Yao Y Y,Zhao Y.Attribute reduction in decision-theoretic rough set models[J].Information Sciences,2008,178(17):3356-3373. 被引量:1

引证文献2

二级引证文献18

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部