Dynamic Credibility Models

Dynamic Credibility Models is a formal inferential framework within credibility theory that distinguishes itself by integrating time-varying parameters and adaptive learning mechanisms to dynamically update credibility estimates in response to evolving data patterns.

8

Publications

233

Citations

25

Authors

14

Institutions

Publications per year

2017–2026

5

Authors

25

  1. XL
    Xia Liu

    Instituto Andaluz de Ciencias de la Tierra, Spain

    1 publications · 25 citations

    1

    h-index

  2. EH
    Enrique Herrera‐Viedma

    Universidad de Granada, Spain

    1 publications · 25 citations

    1

    h-index

  3. YX
    Yejun Xu

    Hohai University, China

    1 publications · 25 citations

    1

    h-index

  4. ML
    Mengqi Li

    Hohai University, China

    1 publications · 25 citations

    1

    h-index

  5. JP
    Jean Pinquet

    Université Paris Nanterre, France

    1 publications · 19 citations

    1

    h-index

1–5 of 25

Venues

  1. Astin Bulletin

    1 publications · 36 citations

    1

    h-index

  2. IEEE Transactions on Fuzzy Systems

    TFS · 1 publications · 25 citations

    1

    h-index

  3. Information Sciences

    1 publications · 33 citations

    1

    h-index

  4. Journal of Simulation

    JOS · 1 publications · 24 citations

    1

    h-index

  5. Applied Mathematics and Computation

    1 publications · 27 citations

    1

    h-index

1–5