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基于粗糙集的决策规则设计算法研究 被引量:1

Study on algorithm of decision rules design based on rough set
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摘要 从获取确定性决策规则的角度出发,基于粗糙集对高维知识库的决策规则约减知识,采用相关方法设计决策规则实现的算法。在不损失信息量的前提下,使决策规则的表示简单化。使用这种算法生成决策规则的时间大大减少,与白钡窑实际控制的数据相比,决策规则控制的误差小于±1。 In the view of certain decision-rule,an algorithm of decision-rule performance is introduced underlying decision-rules reduction knowledge of rough set.It is designed by approaches related to high-dimension database.By the approach,time of decision-rule generated is cut sharply,and error margin of decision-rule control,compares with practical control,is restricted in small zone.
出处 《计算机工程与应用》 CSCD 北大核心 2007年第30期209-212,共4页 Computer Engineering and Applications
关键词 确定性决策规则 规则约减 属性值约减 简化算法 certain decision-rule rules reduction attribute-value reduction simplification algorithm
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参考文献10

  • 1Pawlak Z.Theorize with data using rough sets [C]//Proceedings of the 26th Annual International Computer Software and Applications Conference, IEEE, 2002.
  • 2Pawlak Z.Rough set theory for intelligent industrial applications[C]// IEEE, 1999: 37-44.
  • 3蒙祖强,蔡自兴.个性化决策规则的发现:一种基于Rough Set的方法[J].控制与决策,2004,19(9):994-998. 被引量:10
  • 4马廷淮,赵亚伟,张海盛,曾振柄.基于粗糙集的决策规则约简[J].计算机工程,2003,29(12):5-7. 被引量:7
  • 5Hassanien Aboul-Ella.Rough set approach for attribute reduction and rule generation:a case of patients with suspected breast cancer[EB/OL].Wiley Periodicals Inc.[200g-04-23].http://www.interscience.wiley.com.
  • 6Khan A,Revett K.Data mining the PIMA dataset using rough set theory with a special emphasis on rule reduction [C]//INMIC 2004, IEEE, 2004: 334-339.
  • 7Zdzislaw Pawlak.Rough sets-theoretical aspects of reasoning about data[M].Dordrecht: Kluwer Academic Publishers, 1991 : 51-111.
  • 8刘清.Rough集及Rough推理[M].北京:科学出版社,2003..
  • 9He Ai-jing,Zhu Yao-yao,Mazlack L J.Data discovery using rough set based reductive partitioning:some experiments[C]//IEEE,2001: 203-208.
  • 10邓九英,毛宗源,徐宁.基于粗糙集属性变分区的属性约简[J].华南理工大学学报(自然科学版),2006,34(9):50-55. 被引量:7

二级参考文献28

  • 1[1]Perng Chang-Shing, Wang Haixun, Ma Sheng, et al.User-directed explorarion of mining space with multiple attribustes [A]. In the 2nd IEEE Int Conf on Data Mining (ICDM)[C]. Maebashi, 2002. 394-401.
  • 2[2]Bayardo R J, Agrawal R. Mining the most interseting rules [A]. Proc of 5th Int ACM SIGKDD Int Conf Knowledge Discovery Data Mining [C]. San Diego,1999. 145-154.
  • 3[4]Zhao K, Wang J. A reduction algorithm meeting users′ requirements [J]. J of Computer Science and Technology, 2002, 17(5): 578-593.
  • 4Liau Churnjung.An Overview of Rough Set Semantics for Modal and Quantifier Logics[J],International Journal of Uncertainty,Fuzziness and Knowledge-based Systems,2000,8( 1 ):93-118.
  • 5Raghavan V V,Sever H.The State of Rough Sets for Database Mining Applications[C].In:Proceedings of 23rd Computer Science Conference Workshop on Rough Sets and Database Mining (Lin T Y ed.), 1995-03:1-11.
  • 6Dutsch I.A Logic for Rough Sets[J]. Theoretical Computer Science(B),1997,179:427-436.
  • 7Hu X.Knowledge Discovery in Databases:An Attribute-oriented Rough Set Approach[D].Doctoral Dissertation,University of Regina,Canada,1995.
  • 8Pawlak Z,Grzymada-Busse J,Slowinski R,et al.Rough sets[J].Communications of ACM,1995,38(11):89-95.
  • 9Pawlak Z.Rough sets and data analysis[C]∥Procee-dings of the 1996 Asian Fuzzy Systems Symposium:Soft Computing in Intelligent Systems and Information Proces-sing.Kenting:[s.n.],1996:1-6.
  • 10Pawlak Z.Why rough sets?[C]∥Proceedings of Fifth IEEE International Conference on Fuzzy Systems.New Orleans:[s.n.],1996:738-743.

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