@article{ART002871676},
author={Seungho Lee and Changkyu Lim and Chaehwa Lee and Yongjoo Cho and Jaeoh Kim},
title={Development of standard loss analysis model using big data: Focusing on Republic of Korea army},
journal={Journal of Advances in Military Studies},
issn={2635-5531},
year={2022},
volume={5},
number={2},
pages={159-172},
doi={10.37944/jams.v5i2.158}
TY - JOUR
AU - Seungho Lee
AU - Changkyu Lim
AU - Chaehwa Lee
AU - Yongjoo Cho
AU - Jaeoh Kim
TI - Development of standard loss analysis model using big data: Focusing on Republic of Korea army
JO - Journal of Advances in Military Studies
PY - 2022
VL - 5
IS - 2
PB - Institute of Defense Acquisition Program
SP - 159
EP - 172
SN - 2635-5531
AB - The Republic of Korea Army conducts simulations during peacetime using ground operation resource requirements analysis model (GORRAM) to determine potential losses when at war based on the latest operation plan. Although war-game simulation can yield reliable results, it takes considerable amount of time and effort to build a database and generate scenarios. Therefore, a study is required to supplement the detailed war-game simulation method to quickly determine expected losses. Using data built-in GORRAM, we tested the significance of four factors using beta regression analysis. While multiple regression is most commonly used to model the causality, beta regression is a powerful method for modeling response variables in the (0,1) range, such as the loss ratio. We verified that three factors, namely ‘topography’, ‘operational posture’, and ‘friend/foe power ratio’ were related to loss. This study proposes a new method for calculating the expected loss in real-time, overcoming a limitation of existing war-game simulation methods.
KW - war time resource requirement analysis;ground operation resource requirements analysis model (GORRAM);standard loss analysis model;weapon effectiveness index
DO - 10.37944/jams.v5i2.158
ER -
Seungho Lee, Changkyu Lim, Chaehwa Lee, Yongjoo Cho and Jaeoh Kim. (2022). Development of standard loss analysis model using big data: Focusing on Republic of Korea army. Journal of Advances in Military Studies, 5(2), 159-172.
Seungho Lee, Changkyu Lim, Chaehwa Lee, Yongjoo Cho and Jaeoh Kim. 2022, "Development of standard loss analysis model using big data: Focusing on Republic of Korea army", Journal of Advances in Military Studies, vol.5, no.2 pp.159-172. Available from: doi:10.37944/jams.v5i2.158
Seungho Lee, Changkyu Lim, Chaehwa Lee, Yongjoo Cho, Jaeoh Kim "Development of standard loss analysis model using big data: Focusing on Republic of Korea army" Journal of Advances in Military Studies 5.2 pp.159-172 (2022) : 159.
Seungho Lee, Changkyu Lim, Chaehwa Lee, Yongjoo Cho, Jaeoh Kim. Development of standard loss analysis model using big data: Focusing on Republic of Korea army. 2022; 5(2), 159-172. Available from: doi:10.37944/jams.v5i2.158
Seungho Lee, Changkyu Lim, Chaehwa Lee, Yongjoo Cho and Jaeoh Kim. "Development of standard loss analysis model using big data: Focusing on Republic of Korea army" Journal of Advances in Military Studies 5, no.2 (2022) : 159-172.doi: 10.37944/jams.v5i2.158
Seungho Lee; Changkyu Lim; Chaehwa Lee; Yongjoo Cho; Jaeoh Kim. Development of standard loss analysis model using big data: Focusing on Republic of Korea army. Journal of Advances in Military Studies, 5(2), 159-172. doi: 10.37944/jams.v5i2.158
Seungho Lee; Changkyu Lim; Chaehwa Lee; Yongjoo Cho; Jaeoh Kim. Development of standard loss analysis model using big data: Focusing on Republic of Korea army. Journal of Advances in Military Studies. 2022; 5(2) 159-172. doi: 10.37944/jams.v5i2.158
Seungho Lee, Changkyu Lim, Chaehwa Lee, Yongjoo Cho, Jaeoh Kim. Development of standard loss analysis model using big data: Focusing on Republic of Korea army. 2022; 5(2), 159-172. Available from: doi:10.37944/jams.v5i2.158
Seungho Lee, Changkyu Lim, Chaehwa Lee, Yongjoo Cho and Jaeoh Kim. "Development of standard loss analysis model using big data: Focusing on Republic of Korea army" Journal of Advances in Military Studies 5, no.2 (2022) : 159-172.doi: 10.37944/jams.v5i2.158