Rough Set Model for Cognitive Expectation Embedded Interval-Valued Decision Systems

被引:1
作者
Dai Jianhua [1 ,2 ]
Liu Zhenbo [1 ]
Hu Hu [2 ]
Shi Hong [1 ]
机构
[1] Tianjin Univ, Sch Comp Sci & Technol, Tianjin 300350, Peoples R China
[2] Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310027, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Rough set; Interval-valued decision system with cognitive expectation; Attribute reduction; FEATURE-SELECTION;
D O I
10.1049/cje.2017.09.024
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Interval-valued information system is a kind of knowledge representation model for uncertain information. An interval-valued attribute has an expectation by experience or background knowledge, called cognitive expectation. There are few studies aiming at interval-valued attributes with cognitive expectations. We propose the concept of Interval-valued decision system with expectations (IDSE). A new dominance relation based on the distances between expectations and interval values is constructed, Based on the constructed dominance relation, a rough set model for IDSE is investigated. Attribute reduction in IDSE is also examined by using discernibility matrices and discernibility functions.
引用
收藏
页码:675 / 679
页数:5
相关论文
共 50 条
  • [21] Acquisition of optimal credible rules in ordered interval-valued decision systems
    Xie J.
    Song Y.
    Chen J.
    Sun H.
    Yang X.
    Jiangsu Daxue Xuebao (Ziran Kexue Ban) / Journal of Jiangsu University (Natural Science Edition), 2010, 31 (02): : 210 - 214
  • [22] Analysis of interval-valued decision formal contexts
    Wang, Hong
    Cui, Pin-Zhi
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2015, 29 (04) : 1565 - 1574
  • [23] Interval-Valued Intuitionistic Fuzzy Soft Rough Approximation Operators and Their Applications in Decision Making Problem
    Anjan Mukherjee
    Abhik Mukherjee
    Annals of Data Science, 2022, 9 : 611 - 625
  • [24] Interval-Valued Intuitionistic Fuzzy Soft Rough Approximation Operators and Their Applications in Decision Making Problem
    Mukherjee A.
    Mukherjee A.
    Annals of Data Science, 2022, 9 (03): : 611 - 625
  • [25] Incremental updating of rough approximations in interval-valued information systems under attribute generalization
    Zhang, Yingying
    Li, Tianrui
    Luo, Chuan
    Zhang, Junbo
    Chen, Hongmei
    INFORMATION SCIENCES, 2016, 373 : 461 - 475
  • [26] KNOWLEDGE REDUCTION IN LATTICE-VALUED INFORMATION SYSTEMS WITH INTERVAL-VALUED INTUITIONISTIC FUZZY DECISION
    Xu, Wei-Hua
    Liu, Shi-Hu
    Yu, Fu-Sheng
    INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 2013, 22 (01)
  • [27] Feature selection using a weighted method in interval-valued decision information systems
    Xiaoyan Zhang
    Zongying Jiang
    Weihua Xu
    Applied Intelligence, 2023, 53 : 9858 - 9877
  • [28] Knowledge modeling based on interval-valued fuzzy rough set and similarity inference: prediction of welding distortion
    Feng, Zhi-qiang
    Liu, Cun-gen
    Huang, Hu
    JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE C-COMPUTERS & ELECTRONICS, 2014, 15 (08): : 636 - 650
  • [29] Attribute reductions and concept lattices in interval-valued intuitionistic fuzzy rough set theory: Construction and properties
    Xu, Fei
    Xing, Zhi-Yong
    Yin, Hai-Dong
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2016, 30 (02) : 1231 - 1242
  • [30] Fast algorithms for computing rough approximations in set-valued decision systems while updating criteria values
    Luo, Chuan
    Li, Tianrui
    Chen, Hongmei
    Lu, Lixia
    INFORMATION SCIENCES, 2015, 299 : 221 - 242