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基于程度不可区分关系的粗糙集模型 被引量：1

Rough Set Model Based on Grade Indiscernibility Relation
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摘要 不可区分关系是粗糙集理论的基础。针对信息系统,提出了程度不可区分关系的概念来刻画信息系统中对象的可区分性程度的差异。提出了基于程度不可区分关系的粗糙集模型,并讨论了模型的基本性质,最后研究了基于程度不可区分关系的粗糙近似算子与Pawlak近似算子的关系。 The indiscernibility relation is a key notion of rough set theory. We proposed the grade indiscernibility relation for information system to characterize the difference between the grades of discernibility. The rough set model based on grade indiscernibility relation was presented with its basic properties being discussed. Furthermore, the relationship between grade approximation operators and Pawlak approximation operators was analyzed.
作者 秦克云 罗珺方
机构地区 西南交通大学数学学院
出处 《计算机科学》 CSCD 北大核心 2015年第8期240-243,共4页 Computer Science
基金 国家自然科学基金(61473239 61175044 61175055) 中央高校基础研究基金(2682014ZT28)资助
关键词 粗糙集 程度不可区分关系 粗糙近似算子 模糊关系 Rough set, Grade indiscernibility relation, Rough approximation operator, Fuzzy relation
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献16

  • 1Pawlak Z. Rough set [J]. International Journal of Computer and Information Science, 1982,11 : 341-356.
  • 2Pawlak Z. Rough set: theoretical aspects of reasoning about data [M]. Boston: Kluwer Academic Publishers, 1991.
  • 3Skowron A, Rauszer C. The discernibility matrices and functions in information systems[C]//Slowinski R, ed. Intelligent Deci- sion Support-Handbook of AppUcations and Advances of the Rough Sets Theory. London: Kluwer Academic Publishers,1992:331-362.
  • 4Marzena K. Comparative study of alternative types of knowledge reduction in inconsistent systems [J]. International Journal of Intelligent Systems, 2001,16 : 105-120.
  • 5秦克云,赵华,裴峥.基于广义不可区分关系的决策表约简[J].西华大学学报（自然科学版）,2013,32(4):1-4. 被引量：3
  • 6Kryszkiewicz M. Rough set approach to incomplete information systems [J]. Information Sciences, 1998,112 : 39-49.
  • 7Kryszkiewicz M. Rules in incomplete information Systems[J]. Information Sciences, 1999,113 .. 271-292.
  • 8王国胤.Rough集理论在不完备信息系统中的扩充[J].计算机研究与发展,2002,39(10):1238-1243. 被引量：303
  • 9Bonikowski Z, Bryniarski E, Wybraniec U. Extensions and in-tentions in the rough set theory [J]. Information Sciences, 1998,107 149-167.
  • 10Yao Y Y. Constructive and algebraic methods of theory of rough sets [J]. Information Sciences, 1998,109 .. 21-47.

二级参考文献20

  • 1宋笑雪,解争龙,张文修.集值决策信息系统的知识约简与规则提取[J].计算机科学,2007,34(4):182-184. 被引量：27
  • 2Pawlak Z. Rough set[J]. International Journal of Computer and Information Science, 1982, 11:341 - 356.
  • 3Pawlak Z. Rough Set: Theoretical Aspects of Reasoning about Data [M]. Boston: Kluwer Academic Publishers, 1991.
  • 4Bonikowski Z, Bryniarski E, Wybraniec U. Extensions and In- tentions in the Rough Set Theory [J] Information Sciences, 1998, 107 : 149 - 167.
  • 5Yao Y Y. Constructive and Algebraic Methods of Theory of Rough Sets [ J]. Information Sciences, 1998, 109:21 -47.
  • 6Dubois D, Prade H. Rough Fuzzy Set and Fuzzy rough Sets [ J]. International Journal of General Systems, 1990, 17:191 - 209.
  • 7Zhang X H, Zhou B, Li P. A General Frame for Intuitionistic Fuzzy Rough Sets [ J]. Information Sciences, 2012, 216:34 -49.
  • 8Skowron A, Rauszer C. The Discemibility Matrices and Func- tions in Information Systems [ C ]// In : R. Slowinski ( Ed. ). Intelligent Decision Support-Handbook of Applications and Advances of the Rough Sets Theory. London :Kluwer Academic Publishers,1992:331 -362.
  • 9Marzena K. Comparative Study of Alternative Types of Knowl- edge Reduction in Inconsistent Systems [ J ]. International Journal of In- telligent Systems, 2001, 16 : 105 - 120.
  • 10Kryszkiewicz M. Rough Set Approach to Incomplete Informa- tion Systems [ J ]. Information Sciences, 1998, 112:39 - 49.

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计算机科学
2015年 第8期

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