Explainable Machine Learning for Risk‐Driven Forecasting of Global Food Commodity Prices: Geopolitical, Logistic, and Energy Drivers

Foued Saâdaoui, Hana Rabbouch

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DOI: 10.1111/risa.70405
Published: 2026-11
Container: Risk Analysis
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1111/risa.70405,
  title = {Explainable Machine Learning for Risk‐Driven Forecasting of Global Food Commodity Prices: Geopolitical, Logistic, and Energy Drivers},
  author = {Foued Saâdaoui and Hana Rabbouch},
  year = {2026},
  journal = {Risk Analysis},
  doi = {10.1111/risa.70405},
  url = {https://doi.org/10.1111/risa.70405}
}

RIS

TY  - JOUR
TI  - Explainable Machine Learning for Risk‐Driven Forecasting of Global Food Commodity Prices: Geopolitical, Logistic, and Energy Drivers
AU  - Foued Saâdaoui
AU  - Hana Rabbouch
PY  - 2026
JO  - Risk Analysis
DO  - 10.1111/risa.70405
UR  - https://doi.org/10.1111/risa.70405
ER  -

APA

Saâdaoui, F., & Rabbouch, H. (2026). Explainable Machine Learning for Risk‐Driven Forecasting of Global Food Commodity Prices: Geopolitical, Logistic, and Energy Drivers. Risk Analysis. https://doi.org/10.1111/risa.70405

Source records

crossref · retrieved 2026-11-03T18:17:40.628Z