南京大学学报(自然科学版) ›› 2019, Vol. 55 ›› Issue (4): 537–545.doi: 10.13232/j.cnki.jnju.2019.04.003

所属专题: 测试专题

• • 上一篇    下一篇

模糊三支概念分析与模糊三支概念格

龙柄翰1,徐伟华2()   

  1. 1. 重庆理工大学理学院,重庆,400054
    2. 西南大学人工智能学院,重庆,400715
  • 收稿日期:2019-05-17 出版日期:2019-07-30 发布日期:2019-07-23
  • 通讯作者: 徐伟华 E-mail:chxuwh@gmail.com
  • 基金资助:
    西南大学中央高校基本科研业务专项(XDJK2019B029)

Fuzzy three⁃way concept analysis and fuzzy three⁃way concept lattice

Binghan Long1,Weihua Xu2()   

  1. 1. School of Science, Chongqing University of Technology, Chongqing, 400054, China
    2. College of Artificial Intelligence, Southwest University, Chongqing, 400715, China
  • Received:2019-05-17 Online:2019-07-30 Published:2019-07-23
  • Contact: Weihua Xu E-mail:chxuwh@gmail.com

摘要:

为了进一步将模糊集合理论引入到三支概念分析中,在模糊形式背景下研究了属性导出模糊三支概念与对象导出模糊三支概念,将已有的经典三支概念拓展到了模糊三支概念中,对完善三支概念理论有重要意义.首先,在模糊形式背景下,结合模糊集合理论将对象与属性的关系用隶属度表示.然后,用阈值α以及三支决策思想,将外延(内涵)分为正域,负域,边界域三个部分.其次,提出了两种模糊三支概念(属性导出三支概念与对象导出三支概念)的相关定义和重要定理.最后,结合实例详细解释了模糊三支概念在实际生活中的应用.模糊三支概念分析理论在非经典的背景下为粒计算、人工智能、机器学习等提供了可行的思路.

关键词: 三支决策, 三支概念分析, 模糊形式背景, 模糊集, 模糊三支概念分析

Abstract:

The attribute?induced fuzzy three?way concept and object?induced fuzzy three?way concept is studied in order to further introduce the fuzzy sets theory into the three?way concept analysis under the fuzzy form context. This paper extends the classical three?way concept to the fuzzy three?way concept,which is of great significance to improve the three?way concept theory. Firstly,the relationship between object and attribute is expressed by membership degree combined with the fuzzy sets theory under the fuzzy form context. Then we use threshold α and three?way decisions to divide the extension (intension) into three parts: positive domain,negative domain and boundary domain. Next,we proposed the relevant definitions and important theorems of two kinds of fuzzy three?way concepts(the attribute induced fuzzy three?way concept and the object induced fuzzy three?way concept). Finally,this paper explains in detail the application of fuzzy three?way concept in real life with examples. Fuzzy three?way concept analysis theory provides feasible ideas for granular computing,artificial intelligence,machine learning and so on under the fuzzy context.

Key words: three?way decisions, three?way concept analysis, fuzzy form context, fuzzy sets theory, fuzzy three?way concept analysis

中图分类号: 

  • TP18,O29

表1

模糊形式背景"

abc
x10.760.820.43
x20.310.690.38
x30.270.310.76
x40.460.950.79
x50.970.030.18

表2

属性导出模糊三支概念(模糊AE-概念)的外延与内涵"

外 延内 涵
AE1(G,G)?
AE2(({x1,0.76},{x5,0.97}),({x2,0.31},{x3,0.27},{x4,0.46}))a
AE3(({x1,0.82},{x2,0.69},{x4,0.95}),({x3,0.31},{x5,0.03}))b
AE4(({x3,0.76},{x4,0.79}),({x1,0.43},{x2,0.38},{x5,0.18}))c
AE5(({x1,0.76}),({x3,0.27})){a,b}
AE6(({x4,0.79}),({x5,0.03})){b,c}
AE7(?,({x2,0.31})){a,c}
AE8(?,?)M

表3

对象导出模糊三支概念(模糊OE?概念)的外延与内涵"

内 涵外 延
OE1(M,M)?
OE2(({a,0.76},{b,0.82}),({c,0.43}))x1
OE3(({b,0.69}),({a,0.31},{c,0.38}))x2
OE4(({c,0.76}),({a,0.27},{b,0.31}))x3
OE5(({b,0.95},{c,0.79}),({a,0.46}))x4
OE6(({a,0.97},{b,0.03}),({c,0.18}))x5
OE7(({b,0.69}),({c,0.38})){x1,x2}
OE8(({a,0.76}),({c,0.18})){x1,x5}
OE9(({b,0.69}),({a,0.31})){x2,x4}
OE10(({c,0.76}),({a,0.27})){x3,x4}
OE11(?,({b,0.03})){x3,x5}
OE12(({b,0.69}),?){x1,x2,x4}
OE13(?,({c,0.18})){x1,x2,x5}
OE14(?,({a,0.27})){x2,x3,x4}
OE15(?,?)G

图1

模糊AE?概念格"

图2

模糊OE?概念格"

1 刘盾,李天瑞,李华雄. 粗糙集理论:基于三支决策视角. 南京大学学报(自然科学),2013,49(5):574-581.
Liu D,Li T R,Li H X. Rough set theory:a three?way decisions perspective. Journal of Nanjing University (Natural Sciences),2013,49(5):574-581.
2 刘盾,梁德翠. 广义三支决策与狭义三支决策. 计算机科学与探索,2017,11(3):502-510.
Liu D,Liang D C.Generalized three?way decisions and special three?way decisions. Computer Science and Exploration,2017,11(3):502-510.)
3 YaoY Y. Granular computing and sequential three?way decisions∥Lingras P,Wolski M,Cornelis C,et al. Rough Sets and Knowledge Technology. Springer Berlin Heidelberg,2013:16-27.
4 ZhangQ H,LvG X,ChenY H,et al. A dynamic three?way decision model based on the updating of attribute values. Knowledge?Based Systems,2017,142:71-84.
5 MaX A,YaoY Y. Three?way decision perspectives on class?specific attribute reducts. Information Sciences,2018,450:227-245.
6 GanterB,WilleR. Formal concept analysis:mathematical foundations. New York:Springer?Verlag,1999:12-43.
7 PrissU. Formal concept analysis in information science. Annual Review of Information Science and Technology,2006,40(1):521-543.
8 张云中,柳迪,张原铭. 基于形式概念分析的知识发现研究态势. 情报科学,2018,36(9):155-160.
Zhang Y Z,Liu D,Zhang Y M.Research trend of knowledge discovery based on formal concept analysis. Information Science,2018,36(9):155-160.
9 曲开社,翟岩慧,梁吉业等. 形式概念分析对粗糙集理论的表示及扩展. 软件学报,2007,18(9):2174-2182.
Qu K S,Zhai Y H,Liang J Y,et al.Representation and extension of rough set theory based on formal concept analysis . Journal of Software,2007,18(9):2174-2182.
10 汪文威,祁建军. 三支概念的构建算法. 西安电子科技大学学报,2017,44(1):71-76.
Wang W W,Qi J J.Algorithm for constructing three?way concepts. Journal of Xidian University,2017,44(1):71-76.
11 WangW,QiJ J. Algorithm for constructing three?way concept. Journal of Xidian University,2017,44(1):71-76.
12 QiJ J,WeiL,YaoY. Three?way formal concept analysis∥International Conference on Rough Sets and Knowledge Technology. Springer Berlin Heidelberg,2014:732-741.
13 李金海,邓硕. 概念格与三支决策及其研究展望. 西北大学学报(自然科学版),2017,47(3):321-329.
Li J H,Deng S.Concept lattice,three?way decisions and their research outlooks. Journal of Northwest University (Natural Science Edition),2017,47(3):321-329.
14 YaoY Y. Interval sets and three?way concept analysis in incomplete contexts. International Journal of Machine Learning and Cybernetics,2017,8(1):3-20.
15 HeX L,LingW,SheY H. L?fuzzy concept analysis for three?way decisions:basic definitions and fuzzy inference mechanisms. International Journal of Machine Learning and Cybernetics,2018,9(11):1857-1867.
16 ZadehL A. Fuzzy logic and approximate reasoning. Synthese,1975,30(3-4):407-428.
17 JuandeaburreA B,Fuentes?GonzálezR. The study of the L?fuzzy concept lattice. Mathware & Soft Computing,1970,1(3): 209-218.
18 胡明涵,张俐,任飞亮. 模糊形式概念分析与模糊概念格. 东北大学学报(自然科学版),2007,28(9):1274-1277.
Hu M H,Zhang L,Ren F L.Fuzzy formal concept analysis and fuzzy concept lattice. Journal of Northeastern University (Natural Science),2007,28(9):1274-1277.
19 刘宗田,强宇,周文等. 一种模糊概念格模型及其渐进式构造算法. 计算机学报,2007,30(2):184-188.
Liu Z T,Qiang Y,Zhou W,et al..A fuzzy concept lattice model and its incremental construction algorithm. Chinese Journal of Computers,2007,30(2):184-188.
20 GanterB,WilleR. Formal concept analysis:mathematical foundations. New York:Springer ?Verlag,1999,284.
[1] 顾萍萍,周献中. 基于概率语言术语集评价的三支决策方法研究[J]. 南京大学学报(自然科学版), 2020, 56(4): 505-514.
[2] 高云樵,马建敏. 变精度区间集概念格[J]. 南京大学学报(自然科学版), 2020, 56(4): 437-444.
[3] 任睿,张超,庞继芳. 有限理性下多粒度q⁃RO模糊粗糙集的最优粒度选择及其在并购对象选择中的应用[J]. 南京大学学报(自然科学版), 2020, 56(4): 452-460.
[4] 徐媛媛,张恒汝,闵帆,黄雨婷. 三支交互推荐[J]. 南京大学学报(自然科学版), 2019, 55(6): 973-983.
[5] 张 婷1,2,张红云1,2*,王 真3. 基于三支决策粗糙集的迭代量化的图像检索算法[J]. 南京大学学报(自然科学版), 2018, 54(4): 714-.
[6] 靳义林1,2*,胡 峰1,2. 基于三支决策的中文文本分类算法研究[J]. 南京大学学报(自然科学版), 2018, 54(4): 794-.
[7]  方 宇1,闵 帆1*,刘忠慧1,杨 新2.  序贯三支决策的代价敏感分类方法[J]. 南京大学学报(自然科学版), 2018, 54(1): 148-.
[8] 赵天娜1,米据生1*,解 滨2,梁美社1,3. 基于多伴随直觉模糊粗糙集的三支决策[J]. 南京大学学报(自然科学版), 2017, 53(6): 1081-.
[9] 张振华1*,林小龙1,甘穗福2,袁申国3,胡 勇4. 一类带参数直觉模糊知识度量方法[J]. 南京大学学报(自然科学版), 2017, 53(6): 1100-.
[10]  张春英1,2,乔 鹏1,2,王立亚1,2*,刘 璐1,2,张建松1,3.  基于概率PS-粗糙集的动态三支决策及应用[J]. 南京大学学报(自然科学版), 2017, 53(5): 937-.
[11]  石素玮1*,谭安辉2.  基于诱导覆盖的粗糙直觉模糊集模型[J]. 南京大学学报(自然科学版), 2017, 53(5): 947-.
[12] 张振华1*,胡 勇2,严玉清3. 一类基于坐标变换的带参数直觉模糊距离构造方法[J]. 南京大学学报(自然科学版), 2017, 53(3): 462-.
[13]  薛占熬1,2*,辛现伟1,2,袁艺林1,2,薛天宇1,2. 基于直觉模糊可能性测度的三支决策模型的研究
[J]. 南京大学学报(自然科学版), 2016, 52(6): 1065-.
[14] 汪 璐,贾修一*,顾雁囡. 三支决策贝叶斯网络分类器[J]. 南京大学学报(自然科学版), 2016, 52(5): 833-.
[15] 翟俊海1*,侯少星2,王熙照1. 粗糙模糊决策树归纳算法[J]. 南京大学学报(自然科学版), 2016, 52(2): 306-.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 阚 威, 李 云. 基于LSTM的脑电情绪识别模型[J]. 南京大学学报(自然科学版), 2019, 55(1): 110 -116 .
[2] 徐扬,周文瑄,阮慧彬,孙雨,洪宇. 基于层次化表示的隐式篇章关系识别[J]. 南京大学学报(自然科学版), 2019, 55(6): 1000 -1009 .
[3] 王冬丽,申俊峰,邱海成,杜佰松,李建平,聂潇,王业晗. 辽宁五龙金矿黄铁矿标型特征研究及深部找矿预测[J]. 南京大学学报(自然科学版), 2019, 55(6): 898 -915 .
[4] 党政,代群威,安超,彭启轩,卓曼他,杨丽君. 静态水蚀条件下自然钙华预制块的溶出特性研究[J]. 南京大学学报(自然科学版), 2019, 55(6): 916 -923 .
[5] 王大洋. 渤南洼陷沙三下亚段烃源岩地球化学特征及差异性研究[J]. 南京大学学报(自然科学版), 2019, 55(6): 924 -933 .
[6] 陈石,张兴敢. 基于小波包能量熵和随机森林的级联H桥多电平逆变器故障诊断[J]. 南京大学学报(自然科学版), 2020, 56(2): 284 -289 .
[7] 王俞策,曹剑,陶柯宇,李二庭,向宝力,施春华. 准噶尔盆地芦草沟组致密油系统油源对比与成藏非均质性研究[J]. 南京大学学报(自然科学版), 2020, 56(3): 322 -337 .