Work

Using mathematical time series models to optimize iraq's oil export predictions

Year: 2025

Type: article

Abstract: This study examined and analyzed monthly data on the volume of Iraq's oil exports for the time period (January 2014 to December 2022) using time series models. The prediction values, which revealed that they are reasonably close to the actual series, serve as evidence of the model's correctness. In this paper, we determined from the results of the data analysis in this study that the integrated autoregressive model of the ARIMA moving average (0,1,1) is the best model for representing the data under study after several analysis models are applied to a sample of oil revenues over a nine-year period. The predicted values for the years 2023 and 2024 are then extracted

Source: Experimental and Theoretical NANOTECHNOLOGY

DOI: 10.56053/9.s.157

Authors: Manar Naji Ghayyib, Farah Alaa Adnan, Aseel Aboud Jawad, Halah Qahtan Hamdi, Marwah Hadi Sabr Abed

Institutions: University of Baghdad, University of Information Technology and Communications, University of Technology - Iraq

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W4407734220

FWCI: 1.638

Cites:

Cited by: 2

Related to: 10