Rule-based Prediction Models

Rule-Based Prediction Models is a predictive modeling approach in traffic participant behavior forecasting that belongs to the class of deterministic methods relying on predefined logical rules derived from domain knowledge, distinguished by its use of explicit condition-action rules to simulate and predict motion patterns without probabilistic or learned components.

264

Publications

19.9K

Citations

1.1K

Authors

489

Institutions

Publications per year

2017–2026

63

Authors

1.1K

  1. AT
    A. Townsend Peterson

    University of Kansas, United States

    8 publications · 426 citations

    8

    h-index

  2. JK
    Jan Komorowski

    Uppsala University, Sweden

    6 publications · 204 citations

    6

    h-index

  3. EW
    Ewout W. Steyerberg

    Erasmus MC, Netherlands

    6 publications · 398 citations

    6

    h-index

  4. DE
    Diederick E. Grobbee

    University Medical Center Utrecht, Netherlands

    4 publications · 298 citations

    4

    h-index

  5. CH
    Changhua Hu

    Xi'an High Tech University, China

    4 publications · 203 citations

    4

    h-index

1–5 of 1.1K

Venues

  1. IEEE Transactions on Fuzzy Systems

    TFS · 5 publications · 309 citations

    5

    h-index

  2. Acta Paediatrica

    5 publications · 252 citations

    5

    h-index

  3. Expert Systems with Applications

    4 publications · 106 citations

    4

    h-index

  4. 4

    h-index

  5. PLoS ONE

    3 publications · 240 citations

    3

    h-index

1–5