Time Series Prediction using Box-Jenkins Models

Abdslam K. Suliman , Alsaidi M. Altaher , Najat A.Karami , Marwa A.Matar (1)
(1) , Libya

Abstract

This study aimed to develop a standard model for predicting the production of improved seeds for Tessawa production project using the Box-Jenkins methodology. The Akaike's Information Criterion (AIC) was used to select the appropriate model. Results indicated that the appropriate model for representing the hard wheat series is ARIMA(0.1.3) and ARIMA(0.1.1) for soft wheat and ARIMA(0.2.2) for barley series. After choosing the best model, production was predicted until 2026, which constitutes a sound scientific basis for the development of future plans for the project to help decision-makers make the right decisions.

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Authors

Abdslam K. Suliman , Alsaidi M. Altaher , Najat A.Karami , Marwa A.Matar
عبدالسلام كامل سليمان و السعيدي المهدي الطاهر و نجاة محمد أحمد كرمي و مروة إبراهيم المهدي مطر. (2018). Time Series Prediction using Box-Jenkins Models. Journal of Pure & Applied Sciences, 17(3). https://doi.org/10.51984/jopas.v17i3.285

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