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A Study on Accident Prediction Models for Chemical Accidents Using the Logistic Regression Analysis Model

로지스틱회귀분석 모델을 활용한 화학사고 사상사고 예측모형 개발 연구

  • Lee, Tae-Hyung (National Institute of Chemical Safety) ;
  • Park, Choon-Hwa (National Institute of Chemical Safety) ;
  • Park, Hyo-Hyeon (National Institute of Chemical Safety) ;
  • Kwak, Dae-Hoon (School of Integrated National Security & Dept. of Crime & Forensic Science, Chungnam National Univ.)
  • 이태형 (화학물질안전원) ;
  • 박춘화 (화학물질안전원) ;
  • 박효현 (화학물질안전원) ;
  • 곽대훈 (충남대학교 국가안보융합학부& 과학수사학과)
  • Received : 2019.08.26
  • Accepted : 2019.11.01
  • Published : 2019.12.31

Abstract

Through this study, we developed a model for predicting chemical accidents lead to casualties. The model was derived from the logistic regression analysis model and applied to the variables affecting the accident. The accident data used in the model was analyzed by studying the statistics of past chemical accidents, and applying independent variables that were statistically significant through data analysis, such as the type of accident, cause, place of occurrence, status of casualties, and type of chemical accident that caused the casualties. A significance of p < 0.05 was applied. The model developed in this study is meaningful for the prevention of casualties caused by chemical accidents and the establishment of safety systems in the workplace. The analysis using the model found that the most influential factor in the occurrence of casualty in accidents was chemical explosions. Therefore, there is an urgent need to prepare countermeasures to prevent chemical accidents, specifically explosions, from occurring in the workplace.

본 연구를 통해 화학사고 사상사고 예측모형을 개발하였다. 모형은 로지스틱회귀분석 모델을 활용하여 사상사고에 영향을 주는 변수를 도출하여 적용하였고, 통계적 검증방법과 오즈비를 활용하여 모형의 신뢰성 및 정확성을 검증하였다. 모형에 활용한 사고 자료는 과거 발생했던 화학사고 통계를 분석하여 활용하였으며, 사고의 유형, 원인, 발생 장소, 사상자 현황 및 사상자를 발생시킨 화학사고 등의 자료 분석을 통해 통계적으로 유의하게 나타난 독립변수(p < 0.05)를 적용하였다. 본 연구에서 개발한 모형은 사업장에서 화학사고로 인해 발생하는 사상사고의 예방 및 안전시스템 구축을 위한 연구로서 의의가 있다고 할 수 있다. 모형에 의한 분석결과 사상사고 발생에 가장 크게 영향을 미치는 변수는 폭발에 의한 화학사고인 것으로 조사되었다. 따라서 사업장에서 발생하는 폭발 유형의 화학사고를 예방하기 위한 대책마련이 시급하다고 판단된다.

Keywords

References

  1. Chemistry Safety Clearing-house (csc.me.go.kr).
  2. Deputy Director General of Safety Environment in the Office for Government Policy Coordination, "Accidents of Harmful Substance's Crisis Management and Direction of Policy" (2013).
  3. Ministry of Environment, "Chemicals control Act" (2015).
  4. H. S. Lee and J. P. Yim, "A Study on Prevention Measure Establishment through Cause Analysis of Chemical Accidents", Journal of the Korean Society Safety, Vol. 32, No. 3, pp. 21-27 (2017). https://doi.org/10.14346/JKOSOS.2017.32.3.21
  5. S. B. Jin and J. W. Lee, "Study on Accident Prediction Models in Urban Railway Casulty Accidents Using Logistic Regression Analysis Model", Journal of the Korean Society for Railway, Vol. 20, No. 4, pp. 482-490 (2017). https://doi.org/10.7782/JKSR.2017.20.4.482
  6. J. H. Kang, K. W. Kim and S. M. Kim, "Development of the U-turn Accident Model at Signalized Intersection in Urban Areas by Logistic Regression Analysis", Journal of the Korean Society on Civil Engineers, Vol. 34, No. 4, pp. 1279-1287 (2014). https://doi.org/10.12652/Ksce.2014.34.4.1279
  7. B. H. Park, J. M. Yang and J. Y. Kim, "Logistic Regression Accident Models by Location in the Case of Cheong-ju 4-Legged Signalized Intersections", Journal of Korea Society of Road Engineers, Vol. 11, No. 2, pp. 17-25 (2009).
  8. X. Yan, E. Radwan and M. Abdelaty, "Characteristics of Rear-end Accidents at Signalized Intersections Using Multiple Logistic Regression Model", Accident Analysis & Prevention, Vol. 37, No. 2, pp. 253-259 (2005). https://doi.org/10.1016/j.aap.2004.09.002
  9. C. W. Park, J. B. Wang, M. S. Kim and D. B. Choi, "Development of Risk Assessment for Railway Casulty Accidents", Journal of Korean Society for Railway, Vol. 12, No. 2, pp. 190-198 (2009).
  10. K. Y. Kim, M. S. Jeon, H. C. Kang and S. K. Lee "Regression Analysis by Example", Free Academy, Seoul, pp. 334-357 (2009).
  11. National Institute of Chemical Safety, "Chemistry Safety Clearing-house (csc.me.go.kr)" (2015).
  12. R. D. Hartley, S. Maddan and J. T. Walker, "Sentencing Practices under the Arkansas Sentencing Guideline Structure", Journal of Criminal Justice, Vol. 34, No. 2, pp. 493-506.
  13. J. T. Walker and S. Maddan, "Statistics in Criminology and Criminal Justice: Analysis and Interpretation", Jones & Bartlett Learning (2013).