Forecasting transitions in the state of food security with machine learning using transferable features.
- DOI
- 10.1016/j.scitotenv.2021.147366
- Published
- 2021-04-27
- Container
- Sci Total Environ
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.scitotenv.2021.147366,
title = {Forecasting transitions in the state of food security with machine learning using transferable features.},
author = {Westerveld JJL and van den Homberg MJC and Nobre GG and van den Berg DLJ and Teklesadik AD and Stuit SM.},
year = {2021},
journal = {Sci Total Environ},
doi = {10.1016/j.scitotenv.2021.147366},
url = {https://doi.org/10.1016/j.scitotenv.2021.147366}
}RIS
TY - JOUR TI - Forecasting transitions in the state of food security with machine learning using transferable features. AU - Westerveld JJL AU - van den Homberg MJC AU - Nobre GG AU - van den Berg DLJ AU - Teklesadik AD AU - Stuit SM. PY - 2021 JO - Sci Total Environ DO - 10.1016/j.scitotenv.2021.147366 UR - https://doi.org/10.1016/j.scitotenv.2021.147366 ER -
APA
JJL, W., MJC, V. D. H., GG, N., DLJ, V. D. B., AD, T., & SM., S. (2021). Forecasting transitions in the state of food security with machine learning using transferable features.. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2021.147366
Source records
- europe-pmc · retrieved 2026-09-25T04:16:04.161Z