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基于相容矩阵的改进属性约简算法 被引量:4

Improved Attribute Reduction Algorithm Based on Tolerance Matrix
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摘要 原属性约简算法在计算相容关系时,存在大量重复计算,从而导致时间复杂度为O(|C|3|U|2)。针对该问题,基于不完备决策表,提出时间复杂度为O(|U|2)的高效相容矩阵计算算法,在此基础上,设计改进的基于相容矩阵的属性约简算法。通过实例证明,当空间复杂度相同时,改进算法的时间复杂度从原有O(|C|3|U|2)降为O(|C|2|U|2)。 When original attribute reduction algorithm calculates tolerance relation,there is much repeatedly calculating consumption.And this leads to O(|C|3|U|2) time complexity.Aiming at this problem,based on incomplete decision table,this paper presents a high efficient tolerance matrix computational algorithm whose time complexity is O(|U|2).On that basis,it designs an improved attribute reduction algorithm based on tolerance matrix.Test proves that the time complexity of improved algorithm is reduced from O(|C|3|U|2) to O(|C|2|U|2) with the same space complexity.
出处 《计算机工程》 CAS CSCD 北大核心 2010年第20期25-27,31,共4页 Computer Engineering
基金 国家自然科学基金资助项目(60573059) 北京市重点学科建设基金资助项目(XK100080537) 广西教育厅基金资助项目(200807MS015)
关键词 粗糙集 属性约简 相容关系矩阵 不完备决策表 Rough Set(RS) attribute reduction tolerance relation matrix incomplete decision table
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  • 1黄兵,周献中,张蓉蓉.基于信息量的不完备信息系统属性约简[J].系统工程理论与实践,2005,25(4):55-60. 被引量:41
  • 2曾黄麟.粗集理论及其应用(修订版)[M].重庆:重庆大学出版社,1998..
  • 3Pawlak Z. Rough Set Approach to Multi-attribute Decision Analysis[J]. European Journal of Operational Research, 1994, 72(5): 443-459.
  • 4Ruskey F. Combinatorial Generation(Working Version)[D]. Victoria, Canada: University of Victoria, 2001.
  • 5Guan J W, Bell D A. Rough Computational Methods for Information Systems[J]. Artificial Intelligence, 1998, 105(1/2): 77-103.
  • 6Wang G Y. Algebra view and information view of rough sets theory[A]. Data Mining and knowledge Discovery: Theory, Tools, and Technology Ⅲ, Proceedings of SPIE [C], 2001,4384:200-207.
  • 7Guan J W, Bell D A, Guan Z. Matrix computation for information systems[J]. Information Sciences, 2001,131:129-156.
  • 8Kryszkiewicz M. Rough set approach to incomplete information systems[J]. Information Sciences.1998,112: 39-49.
  • 9Slowinski R, Vsnderpooten D. A Generalized definition of rough approximations based on similarity[C]. IEEE Trans on Data and Knowledge Engineering, 2000,12(2): 331-336.
  • 10Tzung-Pei Hong, Li-Huei Tseng, Shyue-Liang Wang. Learning Rules from incomplete training examples by rough sets[J]. Expert Systems with Applications, 2002,22: 285-293.

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  • 1徐章艳,刘作鹏,杨炳儒,宋威.一个复杂度为max(O(|C||U|),O(|C^2|U/C|))的快速属性约简算法[J].计算机学报,2006,29(3):391-399. 被引量:234
  • 2Pawlak Z. Rough Set[J]. Communication of the ACM, 1995, 38(11): 89-95.
  • 3Hu Xiaohua, Nick C. Learing in Relational Database: A Rough Set Approach International[J]. Journal of Computational Intelligence, 1995, 11(2): 323-338.
  • 4周波涛.可满足性问题(SAT)的快速算法的研究[D].广东,广州:华南理工大学,2000.
  • 5Pawlak Z. Rough Sets[J]. International Journal of Com- puter and Information Sciences, 1982, 11 (5): 341-356.
  • 6Pawlak Z. Information Storage and Retrieval Systems: Mathematical Foundations[J]. Theoretical Computer Science, 1976, 1(4): 331-354.
  • 7Skowron A, Orlowski M W. The Discernibility Matrices and Functions in Information Systems[M]. [S. 1.]: Kluwer Academic Publishers, 1992.
  • 8David A P, Armin B, Zhu Yunshan. A Satisfiability Procedure for Quantified Boolean Formulae[J]. Discrete Applied Mathematics, 2003, 130(2): 291-328.
  • 9Palopoli L, Fiora P, Pizzuti C. Algorithms for Selective Enumeration of Prime Implicants[J]. Artificial Intelligence, 1999, 111(1-2): 41-72.
  • 10Krzysztof S. Rough Classification of HSV Patients[M]. [S. 1.]: Kluwer Academic Publishers, 1992.

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