@article{ART003263310},
author={Song-hwan Kim and In-Sung Kim},
title={A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique},
journal={Industry Promotion Research},
issn={2466-1139},
year={2025},
volume={10},
number={4},
pages={229-237},
doi={10.21186/IPR.2025.10.4.229}
TY - JOUR
AU - Song-hwan Kim
AU - In-Sung Kim
TI - A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique
JO - Industry Promotion Research
PY - 2025
VL - 10
IS - 4
PB - Industrial Promotion Institute
SP - 229
EP - 237
SN - 2466-1139
AB - Despite its low accident frequency, the petrochemical industry faces a high risk of catastrophic incidents, which can lead to extensive human and material damage, as well as significant societal disruption. The restoration of equipment and affected areas following such accidents is a time-consuming and costly process. This study focuses on work-related injuries (1,236 cases) and fatalities (28 cases) that occurred in the Yeosu National Industrial Complex between 2014 and 2023. This study addresses these challenges by first analyzing the current state of industrial accidents in national industrial complexes, identifying their primary causes, and evaluating existing safety management practices. It then examines domestic and international trends in petrochemical safety management technology. To propose advanced policies and institutional improvements, we introduce a novel industrial accident occurrence model using basic accident data and SHAP. Furthermore, a petrochemical complex workplace safety management model is developed through structural model analysis. This comprehensive approach aims to enhance safety protocols and effectively mitigate risks within the petrochemical sector.
KW - Petrochemical Industry;Industrial Accidents;Safety Management;Yeosu National Industrial;SHAP;Structural Model Analysis
DO - 10.21186/IPR.2025.10.4.229
ER -
Song-hwan Kim and In-Sung Kim. (2025). A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique. Industry Promotion Research, 10(4), 229-237.
Song-hwan Kim and In-Sung Kim. 2025, "A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique", Industry Promotion Research, vol.10, no.4 pp.229-237. Available from: doi:10.21186/IPR.2025.10.4.229
Song-hwan Kim, In-Sung Kim "A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique" Industry Promotion Research 10.4 pp.229-237 (2025) : 229.
Song-hwan Kim, In-Sung Kim. A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique. 2025; 10(4), 229-237. Available from: doi:10.21186/IPR.2025.10.4.229
Song-hwan Kim and In-Sung Kim. "A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique" Industry Promotion Research 10, no.4 (2025) : 229-237.doi: 10.21186/IPR.2025.10.4.229
Song-hwan Kim; In-Sung Kim. A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique. Industry Promotion Research, 10(4), 229-237. doi: 10.21186/IPR.2025.10.4.229
Song-hwan Kim; In-Sung Kim. A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique. Industry Promotion Research. 2025; 10(4) 229-237. doi: 10.21186/IPR.2025.10.4.229
Song-hwan Kim, In-Sung Kim. A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique. 2025; 10(4), 229-237. Available from: doi:10.21186/IPR.2025.10.4.229
Song-hwan Kim and In-Sung Kim. "A Study on Disaster Prediction in the Yeosu National Industrial Complex Using the Explainable AI-Based SHAP Technique" Industry Promotion Research 10, no.4 (2025) : 229-237.doi: 10.21186/IPR.2025.10.4.229
