计算机科学 ›› 2016, Vol. 43 ›› Issue (1): 98-102.doi: 10.11896/j.issn.1002-137X.2016.01.023

• 第五届全国智能信息处理学术会议 • 上一篇    下一篇

序信息系统中基于“逻辑且”和“逻辑或”的双量化粗糙模糊集

胡猛,徐伟华   

  1. 重庆理工大学数学与统计学院 重庆 400054,重庆理工大学数学与统计学院 重庆 400054;南京理工大学高维信息智能感知与系统教育部重点实验室 南京210094
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金项目(61472463,4),重庆市自然科学基金项目(cstc2013jcyjA40051),南京理工大学高维信息智能感知与系统教育部重点实验室基金项目(30920140122006),重庆市教委科技项目(KJ1500941),重庆理工大学研究生创新基金项目(YCX2014236),重庆市研究生科研创新基金项目(CYS15223)资助

Double Quantitative Rough Fuzzy Set Model Based on Logical And Operator and Logical Disjunct Operator in Ordered Information System

HU Meng and XU Wei-hua   

  • Online:2018-12-01 Published:2018-12-01

摘要: 基于“逻辑且”和“逻辑或”两个逻辑算子在序信息系统中建立了一种双量化粗糙模糊集模型,克服了传统“逻辑且”和“逻辑或”粗糙模集模型不能解决模糊对象的问题,使得变精度与程度粗糙集具有更广的应用价值。最后通过超市评价进行案例分析,进一步阐述了研究双量化粗糙模糊集的意义。

关键词: 程度粗糙集,模糊粗糙集,序信息系统,变精度粗糙集

Abstract: A novel rough set model,called double quantitative rough fuzzy set model,was established based on the “logical and operator” and “logical disjunct operator” in ordered information system.It overcomes fuzzy problems which cannot be solved by using traditional “logical and operator” and “logical disjunct operatror” rough model.Some important properties were presented,and significance of the model was shown by the supermarket case study.

Key words: Graded rough set,Fuzzy rough set,Ordered information system,Variable precision rough set

[1] Zadeh L A.Fuzzy Sets and Information Granularity[J].Advances in Fuzzy Set Theory & Application,1996:3-18
[2] Pawlak Z.Rough Sets[J].International Journal of Computer and Information Sciences,1982,11(5):341-356
[3] Zhang Xian-yong.Study on several rough set models and their algorithmsbased on logical combinations of precision and grade [D].Chengdu:Sichuan Normal University,2011(in Chinese)张贤勇.基于精度与程度逻辑组合的几类粗糙集模型及其算法研究[D].成都:四川师范大学,2011
[4] Zhang Xian-yong,Xiong Fang,Mo Zhi-wen.Properties of Approximation Operators of Logical Difference Operation of Grade and Precision[J].Mathematics in Practice and Theory,2011,8(41):209-213
[5] Zhang Xian-yong,Mo Zhi-wen,Xiong Fang,et al.Comparative study of variable precision rough set model and graded rough set model[J].International Journal of Approximate Reasoning,2012,53(1):104-116
[6] Zhang Xian-yong,Miao Duo-qian.Two basic double-quantitative rough set models of precision and grade and their investigation using granular computing [J].International Journal of Approximate Reasoning,2013,54(8):1130-1148
[7] Yu Jiang-huang,Xu Wei-hua.Rough Set Based on Logical Disjunctperation of Variable Precision and Grade in Ordered Information System[J].Journal of Frontiers of Computer Science and Technology,2015,9(1):112-118(in Chinese)余建航,徐伟华.序信息系统下变精度与程度的“逻辑或”粗糙集[J].计算机科学与探索,2015,9(1):112-118
[8] Yao Y Y,Lin T Y.Generalization of rough sets using modal lo-gics[J].Intelligent Automatic and Soft Computing,1996,2:103-120
[9] Zhang W X,Wu W Z,Liang J Y,et al.Rough set theory and method [M].Beijing:Science press,2001(in Chinese)张文修,吴伟志,梁吉业,等.粗糙集理论与方法[M].北京:科学出版社,2001
[10] An A,Shan N,Chan C,et al.Discovering rules for water demand prediction:an enhanced rough-set approach[J].Engineering Application of Artificial Intelligence,1996,9:645-653
[11] Xu Wei-hua,Liu Shi-hu,Wang Qiao-rong.The First Type ofGrade Rough Set Based on Rough Membership Function[C]∥2010 Seventh International Conference System and Knowledge Discovery(FSKD2010).2010:1922-1926
[12] Zhang Xian-yong,Xiong Fang,Mo Zhi-wen.Rought Set Model Based on Logical Or Operation of Precision and Grade[J].Pattern Recognition and Artificial Intelligence,2009,7(9):151-155(in Chinese)张贤勇,熊方,莫志文.精度与程度的逻辑或粗糙集模型[J].模式识别与人工智能,2009,7(9):151-155
[13] Ziarko W.Variable precision rough set model[J].Journal ofComputer and System Sciences,1993,6(1):39-59
[14] Dubois D,Prade H.Rough fuzzy sets and fuzzy rough sets[J].International Journal of General Systems,1990,7:191-209
[15] Xu Wei-hua.Ordered information system and rough set[M].Beijing:Science press,2013(in Chinese)徐伟华.序信息系统与粗糙集[M].北京:科学出版社,2013

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