期刊文献+

快速求正区域的渐增式方法研究 被引量:2

Research on Incremental Method for Fast Computing Positive Region
下载PDF
导出
摘要 正区域是粗糙集理论中的核心概念之一,提高计算正区域算法的效率对于其相关算法的效率有重要的影响。本文提出了一种求正区域的渐增式方法,它能有效地去掉求正区域算法中的一些冗余运算,其计算正区域的时间复杂度为,替换掉该算法的一部分将得到一个属性约简算法,它是高效而往往能满足用户需求的,比较适用于大型数据集。理论结果和实验表明,该方法确实能高效地计算出正区域。 Positive region is one of the basic concepts in rough sets theory . Computing Positive Region effectively is very important for improving the performance of relative algorithms. An incremental method for fast computing positive region is put up with in this paper. This method whose time complexity is can take off some redundant operation. Replacing one part of the method will gain a new algorithm for the reduction of the attributes which is effective and will meet the need of the users. Theoretical analysis and experimental results show that this method can reduce the time complexity effectively,
出处 《微计算机信息》 北大核心 2006年第09Z期266-268,30,共4页 Control & Automation
基金 国家科技成果重点推广项目(No.2003EC000001)资助
关键词 粗糙集 决策表 属性约简 rough set,decision table,attributes deduction
  • 相关文献

参考文献4

二级参考文献26

  • 1王珏,苗夺谦,周育健.关于Rough Set理论与应用的综述[J].模式识别与人工智能,1996,9(4):337-344. 被引量:264
  • 2张文修 等.Rough集理论与方法[M].北京:科学出版社,2001..
  • 3Z Pawlak. Rough sets. International Journal of Computer and Information Science, 1982, 11 (5) : 341 - 356.
  • 4Z Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data. Dordrecht: Kluwer Academic Publishers, 1991.
  • 5A Skowron. Rough sets and Boolean reasoning. In: W Pedrycz ed. Granular Computing: An Emerging Paradigm. New York:Phvsica-Verlag, 2001. 95-124.
  • 6W Ziako. Rough sets: Trends, challenges, and prospects. In: W Ziarko, Y Y Yao eds. Rough Sets and Current Trends in Computing(RSCTC 2000). Berlin: Springer-Verlag, 2001. 1-7.
  • 7A Skowron, C Rauszer. The discernibility matrices and functions in information system. In: R Slowinski ed. Intelligent DecisionSupport Handbook of Applications and Advances of the Rough Sets.Theory. Dordrecht: Kluwer Academic Publishers, 1992. 331-362.
  • 8X H Hu, N Cercone. Learning in relational databases: A rough set approach. International Journal of Computational Intelligence,1995, 11(2): 323-338.
  • 9J Jelonek, K Krawiec, R Slowinski. Rough set reduction of attributes and their domains for neural networks. International Journal of Computational Intelligence, 1995, 11(2): 339-347.
  • 10Jue Wang, Ju Wang. Reduction algorithms based on discernbility matrix: The ordered attributes method. Journal of Computer Science & Technology, 2001, 16(6) : 489-504.

共引文献531

同被引文献10

引证文献2

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