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
Parents
39
Forecasting Corn Yield With Machine Learning Ensembles
Frontiers in Plant Science · 2020 · 252 citations · Full text
Agriculture, Agronomy, Data Science +16
Global crop yield forecasting using seasonal climate information from a multi-model ensemble
Toshichika Iizumi, Yonghee Shin, Wonsik Kim et al. · Climate Services · 2018 · 120 citations · Full text
Agriculture, Agronomy, Crop Sciences +17
1–5 of 39
156
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 156
91

Chinese Academy of Sciences
Beijing, China
4 h-index
11 publications
1.2K citations
Chinese Academy of Agricultural Sciences
Beijing, China
3 h-index
6 publications
226 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
4 publications
104 citations
Central China Normal University
Wuhan, China
2 h-index
4 publications
156 citations
Institute of Agricultural Resources and Regional Planning
Beijing, China
2 h-index
3 publications
100 citations
Joint Research Centre
Ispra, Italy
2 h-index
3 publications
457 citations
Iowa State University
Ames, United States
2 h-index
8 publications
991 citations
Aerospace Information Research Institute
Beijing, China
2 h-index
7 publications
828 citations
1–8 of 91
4 publications · 443 citations
4
h-index
2 publications · 30 citations
2
h-index
2 publications · 179 citations
2
h-index
2 publications · 299 citations
2
h-index
3 publications · 158 citations
2
h-index
1–5