DOI QR코드

DOI QR Code

Compression of the Variables Classifying Domestic Marine Accident Data

  • Park, Deuk-Jin (Division of Marine Production System Management, Pukyong National University) ;
  • Yang, Hyeong-Sun (Division of Navigation Convergence Studies, Korea Maritime and Ocean University) ;
  • Yim, Jeong-Bin (Division of Navigation Science, Mokpo National Maritime University)
  • 투고 : 2021.12.02
  • 심사 : 2021.12.22
  • 발행 : 2022.04.30

초록

Maritime accidents result in enormous economic loss and loss of life; thus, such accidents must be prevented, and risks must be managed to prevent these occurrences Risk management must be based on statistical evidence such as variables. Because calculating when variables increase statistically can be difficult, compressing the designated variables is necessary to use the maritime accident data in Korea. Thus, in this study, variables of marine accident data are compressed using statistical methods. The date, ship type, and marine accident type included in all maritime accident data were extracted, the number of optimal variables was confirmed using the hierarchical clustering analysis method, and the data were compressed. For the compressed variables, the validity of the data use was statistically confirmed using analysis of variance, and the data of the variables identified using the variable compression method were designated. Consequently, among the monthly and yearly data, statistical significance was confirmed in yearly data, and compression was possible. The significance of the data was confirmed in six and eight types of ships and accidents, respectively, and these were compressed. These results can be directly used for prevention or prediction based on past maritime accident data. Additionally, the data range extracted from past maritime accidents and the number of applicable data will be studied in the future.

키워드

과제정보

This work was supported by Pukyong National University Research Fund in 2021 (CD20210999)

참고문헌

  1. Abbassinia, M., Kalatpour, O., Motamedzade, M., Soltanian, A. and Mohammadfam, I.(2020), Dynamic human error assessment in emergency using fuzzy bayesian cream, Journal of Research in Health Sciences, Vol. 20, No. 1, p. e00468. https://doi.org/10.34172/jrhs.2020.03
  2. Bradley P. and Carlin Thomas,(2011), Baysian network analysis, second edition, andrew gelman et al; baysian models for categorical data, peter congdon; baysian methods for data analysis, third edition.
  3. Bowo, L. P. and Furusho, M.(2018), Human error assessment and reduction technique for reducing the number of marine accidents in Indonesia, In Applied Mechanics and Materials, Vol. 874, pp. 199-206. https://doi.org/10.4028/www.scientific.net/AMM.874.199
  4. Cacciabue, P. C.(2004), Human error risk management for engineering systems: A methodology for design, safety assessment, accident investigation and training, Reliability Engineering System and Safety, Vol. 83, pp. 229-240. https://doi.org/10.1016/j.ress.2003.09.013
  5. Chauvin, C., Lardjane, S., Morel, G., Clostermann, J. P. and Langard, B.(2013), "Human and organisational factors in maritime accidents: Analysis of collisions at sea using the HFACS", Accident Analysis and Prevention, Vol. 59, pp. 26-37. https://doi.org/10.1016/j.aap.2013.05.006
  6. Cilibrasi, R. and Vitanyi, P. M.(2005), Clustering by compression, IEEE Transactions on Information theory, Vol. 51, No. 4, pp. 1523-1545. https://doi.org/10.1109/TIT.2005.844059
  7. Friedman, N., Geiger, D. and Goldszmidt, M.(1997), Bayesian network classifiers,. Machine learning, Vol. 29, No. 2, pp. 131-163. https://doi.org/10.1023/A:1007465528199
  8. IMO(2001), Formal Safety Assessment, Report on the Joint MSC/MEPC Working Group on the Human Element and Formal Safety Assessment, MSC 74/WP.19.
  9. Kaplan, S. and Garrick, B. J.(1981), On the quantitative definition of risk. Risk analysis, Vol. 1, No. 1, pp. 11-27. https://doi.org/10.1111/j.1539-6924.1981.tb01350.x
  10. Kirwan, B.(1992), Human error identification in human reliability assessment, Part 1: Overview of approaches. Applied ergonomics, Vol. 23, No. 5, pp. 299-318. https://doi.org/10.1016/0003-6870(92)90292-4
  11. KMST, 2021 Written Verdict. [Online], Available at: https://www.kmst.go.kr/kmst/verdict/writtenVerdict/selectWrittenVerdict.do [Accessed at 10th Mar. 2021].
  12. MATLAB(2019), MATLAB and Statistical Toolbox Release 2018b, The MathWorks, Inc., Natick, Massachusetts, United States.
  13. Montewka, J., Krata, P., Goerlandt, F., Mazaheri, A. and Kujala, P.(2011), Marine traffic risk modelling-an innovative approach and a case study, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, Vol. 225, No. 3, pp. 307-322. https://doi.org/10.1177/1748006X11399988
  14. Park, D. J., Yang, H. S. and Yim, J. B.(2019), A Study on the Estimation of Optimal Probability Distribution Function for Seafarers' Behavior Error, Journal of Navigation and Port Research, Vol. 43, No. 1, pp. 1-8. https://doi.org/10.5394/KINPR.2019.43.1.1
  15. Qiao, W., Liu, Y., Ma, X. and Lan, H.(2021), Cognitive Gap and Correlation of Safety-I and Safety-II: A Case of Maritime Shipping Safety Management. Sustainability, Vol. 13, No. 10, p. 5509. https://doi.org/10.3390/su13105509
  16. Rothblum, A. M.(2000), Human error and marine safety, In: National Safety Council Congress and Expo, Orlando, Florida.
  17. Senders, John, W. and Neville, Moray, P.(1991), Human error: cause, prediction, and reduction, Lawrence Erlbaum Associates, New Jersey, USA. p. 25.
  18. Smith, S. P. and Harrison, M. D.(2002), Improving hazard classification through the reuse of descriptive arguments, In International Conference on Software Reuse, Springer, Berlin, Heidelberg.
  19. Wasserman, L.(2013), All of statistics: a concise course in statistical inference, Springer Science & Business Media.
  20. Yildiz, S., Ugurlu, O., Wang, J. and Loughney, S.(2021), Application of the HFACS-PV approach for identification of human and organizational factors (HOFs) influencing marine accidents, Reliability Engineering & System Safety, Vol. 208, p. 107395. https://doi.org/10.1016/j.ress.2020.107395
  21. Yim, J. B.(2009), Development of Quantitative Risk Assessment Methodology for the Maritime Transportation Accident of Merchant Ship, Journal of Navigation and Port Research, Vol. 33, No. 1, pp. 9-19. https://doi.org/10.5394/KINPR.2009.33.1.009
  22. Yim, J. B.(2017), A Study on the Reduction of Common Words to Classify causes of Marine Accidents, Journal of Navigation and Port Research, Vol. 41, No. 3, pp. 109-118. https://doi.org/10.5394/KINPR.2017.41.3.109