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Strengthening Food Security: A Comparison of Food Import Forecasting Models

Published: 03 April 2024 Publication History

Abstract

Food security relies on factors like availability, access, and stability, often assisted by food imports when local production falters. Importantly, these imports stabilize supplies, mitigate shortages and price volatility, and enhance economic stability. Anticipating import requirements is vital for proactive food security planning. In this case study, we employ multiple forecasting models to predict food import for a large number of products from multiple countries. The results highlight varying algorithm performance across datasets. Traditional statistical models remain highly competitive compared to newer alternatives, especially for shorter time series. Our study introduces a multi-model forecasting approach to predict periodic food imports, a pivotal tool for food authorities.

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Cited By

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  • (2025)Sustainable Agriculture in Food Security Integrating Satellite Data Risk Assessment by Cyberattack Detection: AI ApplicationsRemote Sensing in Earth Systems Sciences10.1007/s41976-025-00194-8Online publication date: 13-Feb-2025
  • (2024)LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series ForecastingProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679527(2271-2281)Online publication date: 21-Oct-2024

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        cover image ACM Conferences
        BDCAT '23: Proceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies
        December 2023
        187 pages
        ISBN:9798400704734
        DOI:10.1145/3632366
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Published: 03 April 2024

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        • (2025)Sustainable Agriculture in Food Security Integrating Satellite Data Risk Assessment by Cyberattack Detection: AI ApplicationsRemote Sensing in Earth Systems Sciences10.1007/s41976-025-00194-8Online publication date: 13-Feb-2025
        • (2024)LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series ForecastingProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679527(2271-2281)Online publication date: 21-Oct-2024

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