Ordinal belief entropy

被引:1
|
作者
He, Yuanpeng [1 ]
Deng, Yong [1 ]
机构
[1] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu 610054, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Ordinal belief entropy; Uncertainty; Sequence; INTUITIONISTIC FUZZY-SETS; PERSPECTIVE;
D O I
10.1007/s00500-023-07947-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Entropies are widely applied in measuring the degree of uncertainties existing in frame of discernment. However, all of these entropies regard the frame as a whole that has already been determined, which does not conform to actual situations. In real life, everything comes in a sequence. So, how to measure uncertainties of the dynamic process of determining sequence of propositions contained in a frame of discernment is still an open issue, and no related research has been proceeded. Therefore, a novel ordinal entropy to measure uncertainty of frame of discernment considering the order of propositions is proposed in this paper. Compared with other traditional entropies, it manifests effects on degree of uncertainty brought by orders of propositions. For example, assume there exist three propositions, for ordinal belief entropy, the potential categories of situations are C-3(1) C-2(1) C-1(1), which illustrates that the proposed entropy is able to measure more complex environment and more matches actual circumstances. But for other entropies, they have only one certain value for descriptions of actual situations and the ability of measuring environment is limited. In a general rule, if number of propositions is n, then there are Pi(n)(k)=1 C-k(1) categories of description of situations with respect to ordinal belief entropy. Besides, some numerical examples are provided to verify the correctness and validity of the proposed entropy in this paper.
引用
收藏
页码:6973 / 6981
页数:9
相关论文
共 50 条
  • [1] Ordinal belief entropy
    Yuanpeng He
    Yong Deng
    Soft Computing, 2023, 27 : 6973 - 6981
  • [2] Ordinal fuzzy entropy
    He, Y.
    Deng, Y.
    IRANIAN JOURNAL OF FUZZY SYSTEMS, 2022, 19 (03): : 171 - 186
  • [3] Conditional entropy of ordinal patterns
    Unakafov, Anton M.
    Keller, Karsten
    PHYSICA D-NONLINEAR PHENOMENA, 2014, 269 : 94 - 102
  • [4] Information entropy for ordinal classification
    Hu QingHua
    Guo MaoZu
    Yu DaRen
    Liu JinFu
    SCIENCE CHINA-INFORMATION SCIENCES, 2010, 53 (06) : 1188 - 1200
  • [5] Information entropy for ordinal classification
    QingHua Hu
    MaoZu Guo
    DaRen Yu
    JinFu Liu
    Science China Information Sciences, 2010, 53 : 1188 - 1200
  • [6] Ordinal Patterns, Entropy, and EEG
    Keller, Karsten
    Unakafov, Anton M.
    Unakafova, Valentina A.
    ENTROPY, 2014, 16 (12) : 6212 - 6239
  • [7] Information entropy for ordinal classification
    HU QingHua
    Science China(Information Sciences), 2010, 53 (06) : 1188 - 1200
  • [8] On cumulative belief entropy
    Cui, Huizi
    Kang, Bingyi
    PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021), 2021, : 7230 - 7235
  • [9] Considerations on the Information and Entropy of Ordinal Data
    Petrila, Iulian
    Ungureanu, Florina
    Manta, Vasile
    2014 18TH INTERNATIONAL CONFERENCE SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC), 2014, : 732 - 736
  • [10] A New Belief Entropy Based on Deng Entropy
    Wang, Dan
    Gao, Jiale
    Wei, Daijun
    ENTROPY, 2019, 21 (10)