Title: Big data-based predictive model for attendance rate of reserve forces training

Authors: Jungmok Ma

Addresses: Department of Defense Science, Korea National Defense University, Hwangsanbeol-ro, 1040, Nonsan, South Korea

Abstract: While reserve forces are strategically important to deter war in the Republic of Korea (ROK), the training of the reservists is a challenge since they are civilians and difficult to control. In order to tackle the difficulty of predicting the attendance rate of reserve training, this paper proposes a predictive model using Big Data. The current prediction method in the military uses the last year's attendance rate, and one previous study suggests utilising daily weather information without a systematic analysis. This paper aims to test the significance of the predictor variables in the daily attendance rate. Next, to improve the prediction accuracy of the current method, a predictive model with the volume of web search data is proposed. In the case study, statistically significant predictor variables are identified, and the proposed Big Data-based predictive model improves the prediction performance in comparison to the current method with real reserve training data.

Keywords: big data; search query; predictive model; reserve forces; reserve training.

DOI: 10.1504/IJSOI.2025.152324

International Journal of Services Operations and Informatics, 2025 Vol.13 No.2/3/4, pp.385 - 395

Accepted: 27 Dec 2024
Published online: 16 Mar 2026 *

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