TY - GEN
T1 - Strengthening Food Security
T2 - 10th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2023
AU - Mio, Corrado
AU - Shakya, Siddhartha
AU - Khargharia, Himadri
AU - Ruta, Dymitr
AU - Dengur, Subey
AU - Al Shamisi, Aysha Ali Saif
AU - Alawneh, Asma
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/12/4
Y1 - 2023/12/4
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85192199909&partnerID=8YFLogxK
U2 - 10.1145/3632366.3632392
DO - 10.1145/3632366.3632392
M3 - Conference contribution
AN - SCOPUS:85192199909
T3 - 10th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2023
BT - 10th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2023
Y2 - 4 December 2023 through 7 December 2023
ER -