International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 12, Issue 10 (October 2025), Pages: 203-215

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 Original Research Paper

The effect of an accumulation algorithm on the predictive accuracy of ARIMA models

 Author(s): 

 Mubarak H. Elhafian *, Hamid H. Hussien, Abdelmgid O. M. Sidahmed, Muhammed Aljifri

 Affiliation(s):

 Department of Mathematics, College of Science and Arts, King Abdulaziz University, Jeddah, Saudi Arabia

 Full text

    Full Text - PDF

 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0002-3619-1617

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2025.10.021

 Abstract

This study explores the use of the autoregressive integrated moving average (ARIMA) data-driven modeling approach for forecasting peanut yields in Sudan. Two tests were conducted: one using the original dataset and another using accumulated data. The main objective was to improve forecasting accuracy by applying a method that incorporates accumulated data for future predictions. The results, based on a comparison of the two tests, indicate that the proposed approach enhances prediction clarity. Model identification showed an increase in the coefficient of determination, a decrease in the Bayesian information criterion (BIC), and a reduction in the mean absolute error. These outcomes suggest that the proposed method may provide more accurate forecasts and could be useful for forecasting in various fields.

 © 2025 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Forecasting accuracy, ARIMA model, Accumulated data, Time series, Model evaluation

 Article history

 Received 25 December 2024, Received in revised form 2 May 2025, Accepted 3 October 2025

 Acknowledgment

This work was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant no. G: 331-662-1436. The authors, therefore, acknowledge with thanks to DSR technical and financial support. 

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Elhafian MH, Hussien HH, Sidahmed AOM, and Aljifri M (2025). The effect of an accumulation algorithm on the predictive accuracy of ARIMA models. International Journal of Advanced and Applied Sciences, 12(10): 203-215

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 Figures

  Fig. 1  Fig. 2  Fig. 3  Fig. 4  Fig. 5  Fig. 6  Fig. 7  Fig. 8 

 Tables

  Table 1  Table 2  Table 3  Table 4  Table 5  Table 6  Table 7  Table 8  Table 9  Table 10  Table 11  Table 12  Table 13 

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