计算机科学 ›› 2021, Vol. 48 ›› Issue (1): 157-166.doi: 10.11896/jsjkx.191200175
薛占熬, 张敏, 赵丽平, 李永祥
XUE Zhan-ao, ZHANG Min, ZHAO Li-ping, LI Yong-xiang
摘要: 多粒度决策粗糙集是从多角度来处理不确定数据和风险决策问题的重要模型。针对不完备信息系统下的决策分析问题,在多粒度决策粗糙集中引入集对优势关系,对优势度进行了改进,使结果更加合理。然后对多粒度近似空间进行了拓展,提出了集对优势关系下的乐观、悲观、均值、乐观-悲观和悲观-乐观5种多粒度决策粗糙集模型,并讨论了其相关性质以及模型之间的相互关系。结合三支决策理论,在不完备信息系统中用区间值表示损失函数,获得不同的阈值,建立了5个相应的可变三支决策模型,推导出决策规则。最后,通过公司员工评估的案例证明,所提模型在实际应用中灵活性更高,不会过于宽松或过于严格,使最终决策更为合理,从而为不完备信息系统下不确定性问题的决策分析提供了新方法。
中图分类号:
[1] PAWLAK Z.Rough sets[J].International Journal of Computer and Information Sciences,1982,11(5):341-356. [2] YAO Y Y.Probabilistic rough set approximations[J].International Journal of Approximate Reasoning,2008,49(2):255-271. [3] YAO Y Y,WONG S K M.A decision theoretic frame-work for approximating concepts[J].International Journal of Man-machine Studies,1992,37(6):793-809. [4] SLEZAK D,ZIARKO W.The investigation of the Bayesianrough set model[J].International Journal of Approximate Reasoning,2005,40(1/2):81-91. [5] ZIARKO W.Variable precision rough set model[J].Journal of Computer and System Sciences,1993,46(1):39-59. [6] YAO Y Y,LIN T Y.Generalization of rough sets using modal logics[J].Intelligent Automatic and Soft Computing,1996,2(2):103-120. [7] ZHANG X,MEI C L,CHEN D G,et al.A fuzzy rough set based feature selection method using representative instances[J].Knowledge-Based Systems,2018,151(1):216-229. [8] ZHANG L,ZHAN J M,XU Z S.Covering-based generalized IF rough sets with applications to multi-attribute decision-making[J].Information Sciences,2019,478:275-302. [9] CHEN D G,ZHANG X X,WANG X Z,et al.Uncertainty lear-ning of rough set-based prediction under a holistic framework[J].Information Sciences,2018,463-464:129-151. [10] HU M J,YAO Y Y.Structured approximations as a basis for three-way decisions in rough set theory[J].Knowledge-Based Systems,2019,165:92-109. [11] BU Z,WANG Y Y,LI H J,et al.Link prediction in temporal networks:integrating survival analysis and game theory[J].Information Sciences,2019,498:41-61. [12] ZHANG C,LI D Y,MU Y M,et al.An interval-valued hesitant fuzzy multigranulation rough set over two universes model for steam turbine fault diagnosis[J].Applied Mathematical modelling,2017,42:693-704. [13] YAO Y Y.The superiority of three-way decisions in probabilistic rough set models[J].Information Sciences,2011,181(6):1080-1096. [14] LIU D,LIANG D C,WANG C C.A novel three-way decision model based on incomplete information system[J].Knowledge-Based Systems,2016,91:32-45. [15] LIANG D C,XU Z S,LIU D.Three-way decisions with intui-tionistic fuzzy decision-theoretic rough sets based on point ope-rators[J].Information Sciences,2017,375:183-201. [16] QIAN J,DANG C Y,YUE X D,et al.Attribute reduction for sequential three-way decisions under dynamic granulation[J].International Journal of Approximate Reasoning,2017,85:196-216. [17] HU B Q,WONG H,YIU K F C.On two novel types of three-way decisions in three-way decision spaces[J].International Journal of Approximate Reasoning,2017,82:285-306. [18] QIAN Y H,LIANG J Y,YAO Y Y,et al.MGRS:a multi-granulation rough set[J].Information Sciences,2010,180(6):949-970. [19] QIAN Y H,ZHANG H,SANG Y L,et al.Multigranulation decision-theoretic rough sets[J].International Journal of Approximate Reasoning,2014,55(1):225-237. [20] ZHANG Q H,ZHANG Q,WANG G Y.The uncertainty ofprobabilistic rough sets in multi-granulation spaces[J].International Journal of Approximate Reasoning,2016,77:38-54. [21] SANG Y L,QIAN Y H.Granular structure reduction approach to multigranulation decision-theoretic rough sets[J].Computer Science,2017,44(5):199-205. [22] XU Y.Multigranulation rough set model based on granulation of attributes and granulation of attribute values[J].Information Sciences,2018,484:1-13. [23] CHENG Y,LIU Y.Knowledge discovery model based on neighborhood multi-granularity rough sets[J].Computer Science,2019,46(6):224-230. [24] QIAN Y H,LIANG J Y,DANG C Y.Incomplete multigranulation rough set[J].IEEE Transactions on Systems Man and Cybernetics-Part A Systems and Humans,2010,40(2):420-431. [25] LUO G Z,XU X X.Analysis method of multi-granularity decision rough set based on possible degree tolerance relation[J].Application Research of Computer,2019,36(12):3588-3592. [26] HUANG L P.Incomplete ordered information system rough set model based on set-pair dominant degree[J].Journal ofLiao-cheng University(Natural Science Edition),2017,30(1):97-101. [27] XUE Z A,ZHANG M,LI Y X,et al.Double-quantitative gene-ralized multi-granulation set-pair dominance rough sets in incomplete ordered information system[J].Symmetry,2020,12(1):133. [28] LUO C,LI T R,HUANG Y Y,et al.Updating three-way decisions in incomplete multi-scaleinformation systems [J].Information Sciences,2019,476:274-289. [29] CHEN Y X,ZHU P.Extending characteristic relations on an incomplete data set by the three-way decision theory[J].International Journal of Approximate Reasoning,2020,119:108-121. [30] LUO J F,HU M J,QIN K Y.Three-way decision with incomplete information based on similarity and satisfiability[J].International Journal of Approximate Reasoning,2020,120:151-183. |
[1] | 秦琪琦, 张月琴, 王润泽, 张泽华. 基于知识图谱的层次粒化推荐方法 Hierarchical Granulation Recommendation Method Based on Knowledge Graph 计算机科学, 2022, 49(8): 64-69. https://doi.org/10.11896/jsjkx.210600111 |
[2] | 张源, 康乐, 宫朝辉, 张志鸿. 基于Bi-LSTM的期货市场关联交易行为检测方法 Related Transaction Behavior Detection in Futures Market Based on Bi-LSTM 计算机科学, 2022, 49(7): 31-39. https://doi.org/10.11896/jsjkx.210400304 |
[3] | 杨斐斐, 沈思妤, 申德荣, 聂铁铮, 寇月. 面向数据融合的多粒度数据溯源方法 Method on Multi-granularity Data Provenance for Data Fusion 计算机科学, 2022, 49(5): 120-128. https://doi.org/10.11896/jsjkx.210300092 |
[4] | 王志成, 高灿, 邢金明. 一种基于正域的三支近似约简 Three-way Approximate Reduction Based on Positive Region 计算机科学, 2022, 49(4): 168-173. https://doi.org/10.11896/jsjkx.210500067 |
[5] | 胡艳丽, 童谭骞, 张啸宇, 彭娟. 融入自注意力机制的深度学习情感分析方法 Self-attention-based BGRU and CNN for Sentiment Analysis 计算机科学, 2022, 49(1): 252-258. https://doi.org/10.11896/jsjkx.210600063 |
[6] | 张师鹏, 李永忠. 基于降噪自编码器和三支决策的入侵检测方法 Intrusion Detection Method Based on Denoising Autoencoder and Three-way Decisions 计算机科学, 2021, 48(9): 345-351. https://doi.org/10.11896/jsjkx.200500059 |
[7] | 王栋, 周大可, 黄有达, 杨欣. 基于多尺度多粒度特征的行人重识别 Multi-scale Multi-granularity Feature for Pedestrian Re-identification 计算机科学, 2021, 48(7): 238-244. https://doi.org/10.11896/jsjkx.200600043 |
[8] | 李艳, 范斌, 郭劼, 林梓源, 赵曌. 基于k-原型聚类和粗糙集的属性约简方法 Attribute Reduction Method Based on k-prototypes Clustering and Rough Sets 计算机科学, 2021, 48(6A): 342-348. https://doi.org/10.11896/jsjkx.201000053 |
[9] | 王政, 姜春茂. 一种基于三支决策的云任务调度优化算法 Cloud Task Scheduling Algorithm Based on Three-way Decisions 计算机科学, 2021, 48(6A): 420-426. https://doi.org/10.11896/jsjkx.201000023 |
[10] | 吕乐宾, 刘群, 彭露, 邓维斌, 王崇宇. 结合多粒度信息的文本匹配融合模型 Text Matching Fusion Model Combining Multi-granularity Information 计算机科学, 2021, 48(6): 196-201. https://doi.org/10.11896/jsjkx.200700100 |
[11] | 丁玲, 向阳. 基于分层次多粒度语义融合的中文事件检测 Chinese Event Detection with Hierarchical and Multi-granularity Semantic Fusion 计算机科学, 2021, 48(5): 202-208. https://doi.org/10.11896/jsjkx.200800038 |
[12] | 周晓进, 徐陈铭, 阮彤. 面向中文电子病历的多粒度医疗实体识别 Multi-granularity Medical Entity Recognition for Chinese Electronic Medical Records 计算机科学, 2021, 48(4): 237-242. https://doi.org/10.11896/jsjkx.200100036 |
[13] | 陈卓, 王国胤, 刘群. 结合多粒度特征融合的自然场景文本检测方法 Natural Scene Text Detection Algorithm Combining Multi-granularity Feature Fusion 计算机科学, 2021, 48(12): 243-248. https://doi.org/10.11896/jsjkx.201000154 |
[14] | 辛现伟, 史春雷, 韩雨琦, 薛占熬, 宋继华. 基于三支决策的增量标签传播算法 Incremental Tag Propagation Algorithm Based on Three-way Decision 计算机科学, 2021, 48(11A): 102-105. https://doi.org/10.11896/jsjkx.210300065 |
[15] | 薛占熬, 孙冰心, 侯昊东, 荆萌萌. 基于多粒度粗糙直觉犹豫模糊集的最优粒度选择方法 Optimal Granulation Selection Method Based on Multi-granulation Rough Intuitionistic Hesitant Fuzzy Sets 计算机科学, 2021, 48(10): 98-106. https://doi.org/10.11896/jsjkx.200800074 |
|