Using a machine learning approach and big data to augment WASDE forecasts : empirical evidence from US corn yield
| Year of publication: |
2023
|
|---|---|
| Authors: | Roznik, Mitchell ; Mishra, Ashok K. ; Boyd, Milton |
| Published in: |
Journal of forecasting. - New York, NY : Wiley Interscience, ISSN 1099-131X, ZDB-ID 2001645-1. - Vol. 42.2023, 6, p. 1370-1384
|
| Subject: | forecasting crop yield | Google Earth Engine | machine learning | NDVI | weather data | XGBoost | Künstliche Intelligenz | Artificial intelligence | Ernteertrag | Crop yield | Prognoseverfahren | Forecasting model | USA | United States | Big Data | Big data | Wetter | Weather | Maisanbau | Maize production |
-
Corn yield dynamics and weather shocks : climate change implications for the U.S. corn belt
McFadden, Jonathan R., (2020)
-
Early-season estimation of winter wheat yield : a hybrid machine learning-enabled approach
Qiao, Di, (2024)
-
Forecasting inflation in Mongolia using machine learning
Doojav, Gan-Ochir, (2025)
- More ...
-
Kumar, Anjani, (2019)
-
Subsidies under uncertainty : modeling of input- and output-oriented policies
Chen, You-Hua, (2020)
-
Transforming agriculture in South Asia : the role of value chains and contract farming
Mishra, Ashok K., (2021)
- More ...