Random Forests for Global and Regional Crop Yield Predictions

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and r...

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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: Jeong, Jig Han, Resop, Jonathan P., Mueller, Nathaniel D., Fleisher, David H., Yun, Kyungdahm, Butler, Ethan E., Timlin, Dennis J., Shim, Kyo-Moon, Gerber, James S., Reddy, Vangimalla R., Kim, Soo-Hyung
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2016
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC4892571/
https://ncbi.nlm.nih.gov/pubmed/27257967
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0156571
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