Ensemble Yield Forecasting

Ensemble Yield Forecasting is a predictive modeling approach that integrates multiple individual yield forecasting models to improve accuracy and robustness by leveraging their collective performance through statistical or machine learning-based combination techniques.

39

Publications

2.5K

Citations

156

Authors

91

Institutions

Publications per year

2017–2026

33

Authors

156

  1. JT
    Jean‐Michel Terres

    Joint Research Centre, Italy

    2 publications · 275 citations

    2

    h-index

  2. DN
    Dev Niyogi

    Purdue University West Lafayette, United States

    2 publications · 78 citations

    2

    h-index

  3. PC
    Pierre Cantelaube

    Joint Research Centre, Italy

    2 publications · 275 citations

    2

    h-index

  4. AJ
    Andrew J. Challinor

    University of Leeds, United Kingdom

    2 publications · 168 citations

    2

    h-index

  5. TW
    Tim Wheeler

    University of Reading, United Kingdom

    2 publications · 168 citations

    2

    h-index

1–5 of 156

Venues

  1. Tellus A Dynamic Meteorology and Oceanography

    4 publications · 443 citations

    4

    h-index

  2. The Journal of Agricultural Science

    2 publications · 30 citations

    2

    h-index

  3. The Science of The Total Environment

    2 publications · 179 citations

    2

    h-index

  4. Frontiers in Plant Science

    2 publications · 299 citations

    2

    h-index

  5. Agricultural and Forest Meteorology

    3 publications · 158 citations

    2

    h-index

1–5