A Comparison of Advanced Machine Learning Models for Food Import Forecasting

Corrado Mio; Siddhartha Shakya

doi:10.5220/0012998100003837

A Comparison of Advanced Machine Learning Models for Food Import Forecasting

Corrado Mio
, Siddhartha Shakya

Emirates ICT Innovation Center

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Food security is responsible for food availability, access and price stability. Food import is used to ensure availability when local production is inadequate and diversity when local production is not possible. Food import prediction is one of the tools used to ensure food security. In this case study, we analyze Neural Network Forecasting models applied to a food import dataset to understand whether these models, when applied to small time series, perform better than statistical or regression models. And if it is better to use short or long forecast horizons.

Original language	British English
Title of host publication	Proceedings of the 16th International Joint Conference on Computational Intelligence, IJCCI 2024
Editors	Francesco Marcelloni, Kurosh Madani, Niki van Stein, Joaquim Joaquim
Pages	568-575
Number of pages	8
DOIs	https://doi.org/10.5220/0012998100003837
State	Published - 2024
Event	16th International Joint Conference on Computational Intelligence, IJCCI 2024 - Porto, Portugal Duration: 20 Nov 2024 → 22 Nov 2024

Publication series

Name	International Joint Conference on Computational Intelligence
Volume	1
ISSN (Electronic)	2184-3236

Conference

Conference	16th International Joint Conference on Computational Intelligence, IJCCI 2024
Country/Territory	Portugal
City	Porto
Period	20/11/24 → 22/11/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger

Keywords

Food Import
Forecasting
Neural Network
Time Series

Access to Document

10.5220/0012998100003837

OpenUrl availability

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Cite this

Mio, C., & Shakya, S. (2024). A Comparison of Advanced Machine Learning Models for Food Import Forecasting. In F. Marcelloni, K. Madani, N. van Stein, & J. Joaquim (Eds.), Proceedings of the 16th International Joint Conference on Computational Intelligence, IJCCI 2024 (pp. 568-575). (International Joint Conference on Computational Intelligence; Vol. 1). https://doi.org/10.5220/0012998100003837

Mio, Corrado ; Shakya, Siddhartha. / A Comparison of Advanced Machine Learning Models for Food Import Forecasting. Proceedings of the 16th International Joint Conference on Computational Intelligence, IJCCI 2024. editor / Francesco Marcelloni ; Kurosh Madani ; Niki van Stein ; Joaquim Joaquim. 2024. pp. 568-575 (International Joint Conference on Computational Intelligence).

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abstract = "Food security is responsible for food availability, access and price stability. Food import is used to ensure availability when local production is inadequate and diversity when local production is not possible. Food import prediction is one of the tools used to ensure food security. In this case study, we analyze Neural Network Forecasting models applied to a food import dataset to understand whether these models, when applied to small time series, perform better than statistical or regression models. And if it is better to use short or long forecast horizons.",

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author = "Corrado Mio and Siddhartha Shakya",

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year = "2024",

doi = "10.5220/0012998100003837",

language = "British English",

isbn = "9789897587214",

series = "International Joint Conference on Computational Intelligence",

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Mio, C & Shakya, S 2024, A Comparison of Advanced Machine Learning Models for Food Import Forecasting. in F Marcelloni, K Madani, N van Stein & J Joaquim (eds), Proceedings of the 16th International Joint Conference on Computational Intelligence, IJCCI 2024. International Joint Conference on Computational Intelligence, vol. 1, pp. 568-575, 16th International Joint Conference on Computational Intelligence, IJCCI 2024, Porto, Portugal, 20/11/24. https://doi.org/10.5220/0012998100003837

A Comparison of Advanced Machine Learning Models for Food Import Forecasting. / Mio, Corrado; Shakya, Siddhartha.
Proceedings of the 16th International Joint Conference on Computational Intelligence, IJCCI 2024. ed. / Francesco Marcelloni; Kurosh Madani; Niki van Stein; Joaquim Joaquim. 2024. p. 568-575 (International Joint Conference on Computational Intelligence; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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A Comparison of Advanced Machine Learning Models for Food Import Forecasting

Abstract

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Conference

UN SDGs

Keywords

Access to Document

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