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程度上、下近似算子的乘积运算 被引量:3

Product Operation of Grade Upper and Lower Approximation Operators
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摘要 主要探索了程度近似算子的乘积复合运算,定义了程度上、下近似算子的乘积运算,得到了其本质、基本结构与性质,为计算提出了宏观算法与结构算法,进行了算法分析与比较,得到了结构算法在算法时间、算法空间上优于宏观算法的结论.最后用实例进行了说明,并讨论了程度粗糙集模型与变精度粗糙集模型的关系. This paper aims to explore product operation of grade approximation operators. Product operation of grade upper and lower approximation operators is proposed first, and its essence, basic structure and properties are investigated. Macroscopic algorithm and structural algo:rithm are proposed and analyzed to calculate. It is proved that the structural algorithm is better than macroscopic algorithm in terms of algorithm time and algorithm space. Finally, an example is given, and the relationship between graded rough set model and variable precision rough set model is discussed.
出处 《四川师范大学学报(自然科学版)》 CAS CSCD 北大核心 2011年第6期775-779,共5页 Journal of Sichuan Normal University(Natural Science)
基金 国家自然科学基金(11071178) 国家自然科学青年科学基金(60803028) 四川省科技支撑计划项目基金(09ZC1838) 四川省青年基金(10ZB004)资助项目
关键词 人工智能 粗糙集理论 程度粗糙集 程度近似算子 结构算法 宏观算法 artificial intelligence rough set theory graded rough set grade approximation operator structural algorithm macro- scopic algorithm
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参考文献18

  • 1Pawlak Z. Rough sets [ J ]. International J Computer and Information Sciences, 1982,11:341 -356.
  • 2Yao Y Y, Lin T Y. Generalization of rough sets using modal logics[ J ]. Intelligent Automation and Soft Computing, 1996,2 (2) : 103 - 120.
  • 3Ziarko W. Variable precision rough set model[ J]. 3 Computer and System Sciences,1993,46( 1 ) :39 -59.
  • 4张贤勇,莫智文.变精度粗糙集[J].模式识别与人工智能,2004,17(2):151-155. 被引量:43
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  • 6徐伟华,刘士虎,张文修.一般二元关系下基于粗糙隶属函数的程度粗糙集[J].重庆理工大学学报(自然科学),2010,24(10):101-108. 被引量:7
  • 7Xu W H, LiuI S H, Wang Q R, et al. The first type of graded rough set based on rough membership function[ C]//Fuzzy Systems and Knowledge Discovery. New York : IEEE,2010 : 1922 - 1926.
  • 8张贤勇,谢寿才,莫智文.程度粗糙集[J].四川师范大学学报(自然科学版),2010,33(1):12-16. 被引量:15
  • 9成蓉华,陈世联.基于程度粗糙集的知识约简方法[J].昆明理工大学学报(理工版),2006,31(1):119-121. 被引量:3
  • 10戴岱,秦克云,李众立.基于程度粗糙集模型的近似约简和近似相对约简[J].西南科技大学学报,2003,18(4):5-7. 被引量:6

二级参考文献59

共引文献71

同被引文献31

  • 1成蓉华,陈世联.基于程度粗糙集的知识约简方法[J].昆明理工大学学报(理工版),2006,31(1):119-121. 被引量:3
  • 2Pawlak Z.Rough sets[J].International Journal of Computer and Information Sciences,1982,11:341-356.
  • 3Yao Y Y.Relational interpretations of neighborhood operators and rough set approximation operators[J].Information Sciences,1998,111(1-4):239-259.
  • 4Yao Y Y,Lin T Y.Generalization of rough sets using modal logics[J].Intelligent Automation and Soft Computing,1996,2(2):103-120.
  • 5Pawlak Z. Rough sets[ J]. Inter J Comput Info Sci,1982,11 :341 - 356.
  • 6Yao Y Y, Lin T Y. Generalization of rough sets using modal logics[ J]. Intelligent Automation and Soft Computing, 1996,2(2):103 - 120.
  • 7Ziarko W. Variable precision rough set model[ J]. J Comput Syst Sci, 1993 ,46( 1 ) :39 -59.
  • 8Yao Y Y,Lin T Y. Graded rough set approximations based on nested neighborhood systems[ G] //Zimmermann H J. Proceedingsof 5th European Congress on intelligent techniques and Soft computing. Aachen: Verlag Mainz, 1997( 1) :196 -200.
  • 9Xu W H, Liu S H, Wang Q R, et al. The first type of graded rough set based on rough membership function[ C] //Fuzzy Systemsand Knowledge Discovery. New York : IEEE ,2010 ; 1922 — 1926.
  • 10Zhang X Y, Mo Z W, Xiong F. Product operation of grade upper approximation operator and grade lower approximation operatorbased on two parameters [C] //Hu W B, Li X. 2009 International Conference on Information Engineering and Computer Science(ICIECS 2009). New York:IEEE,2009(4) :2564 - 2567.

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