Browse > Article
http://dx.doi.org/10.5394/KINPR.2021.45.3.095

A Statistical Analysis of the Causes of Marine Incidents occurring during Berthing  

Roh, Boem-Seok (Korea Institute of Maritime and Fisheries Technology)
Kang, Suk-Young (Korea Institute of Maritime and Fisheries Technology)
Publication Information
Journal of Navigation and Port Research / v.45, no.3, 2021 , pp. 95-101 More about this Journal
Abstract
Marine Incidents based on Heinrich's law are very important in preventing accidents. However, marine Incident data are mainly qualitative and are used to prevent similar accidents through case sharing rather than statistical analysis, which can be confirmed in the marine Incident-related data posted in the Korea Maritime Safety Tribunal. Therefore, this study derived quantitative results by analyzing the causes of marine incidents during berthing using various methods of statistical analysis. To this end, data involving marine incidents from various shipping companies were collected and reclassified for easy analysis. The main keywords were derived via primary analysis using text mining. Only meaningful words were selected via verification by an expert group, and time series and cluster analysis were performed to predict marine incidents that may occur during berthing. Although the role of an expert group was still required during the analysis, it was confirmed that quantitative analysis of marine incidents was feasible, and iused to provide cause and accident prevention information.
Keywords
marine incidents; qualitative data; statistical analysis; text mining; time series & cluster analysis;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Kim, H. T., Na, S. and Ha, W. H.(2011), "A Case Study of Marine Accident Investigation and Analysis with Focus on Human Error", Journal of the Ergonomics Society of Korea Vol. 30, pp. 137-150.   DOI
2 Korea Association for ICT promotion(2020), Cluster Analysis, http://word.tta.or.kr/dictionary/searchList.do.
3 Jang, J. M., Lee, U. B. and Jung, H. Y.(2019), "Analysis of Marine Safety Impacts Using Social Big Data in Marine Transportation", Journal of Korean Society of Transportation, Vol. 37, No. 2, pp. 148-167.   DOI
4 Lim, C. H.(2010), "A Study on the Introduction of IMO Casualty Investigation Code and Marine Safety Investigation System in Korea", The Journal of Korean Society on Marine Environment & Safety, Vol. 16, No. 1, pp. 57-63.
5 News Jelly(2021), Heat Map, https://post.naver.com/viewer/postView.nhn?volumeNo=29825914&memberNo=35871176&vType=VERTICAL.
6 Doopedia(2020), Time Series Analysis, https://www.doopedia.co.kr/search/encyber/new_totalSearch.jsp.
7 Kang, S. Y. et al.(2018), "An Analysis of Causes of Marine Incidents at sea Using Big Data Technique", The Journal of Korean Society on Marine Environment & Safety, Vol. 24, No. 4, pp. 408-414.   DOI
8 Kim, C. G.(2006), "A Study on the Development of Marine Casualty Forecasting System", Mokpo National Maritime University, 12.
9 Korea Maritime Safety Tribunal(2021), Maritime Accident Statistics, www.kmst.go.kr/kmst/statistics/annualReport/selectAnnualReportList.do.
10 Korea Association for ICT Promotion(2020), Text Mining, http://word.tta.or.kr/dictionary/searchList.do.
11 National Law Information Center(2021), Marine Accidents Inquiry Act, https://www.law.go.kr/lsSc.do?section=&menuId=1&subMenuId=15&tabMenuId=81& eventGubun=060101&query=%ED%95%B4%EC%96%91%EC%82%AC%EA%B3%A0%EC%8B%AC%ED%8C%90%EB%B2%95#undefined.
12 Rho, B. S. et al.(2018), "A Study on the Relation between Marine Incidents and Marine Accidents using Statistical Analysis", Journal of Fisheries and Marine Sciences Education, Vol. 30, No. 4, pp. 1208-1214.   DOI
13 Song, H. W. et al.(2014), "A Study on the Development and Application of Marine Accident Management System", Korean Institute of Navigation Port Research Conference Proceedings, pp. 311-315.
14 Yoon, I. H. and Oh, J. M.(2019), "A study on the development of predictive maintenance system algorithm for ship's core equipment", Conference Proceedings, p. 112.
15 Kim, J. Y. and Kim, D. S.(2016), "A Study on the Method for Extracting the Purpose-Specific Customized Information from Online Product Reviews based on Text Mining", The Journal of Society for e-Business Studies, Vol. 21, No. 2, pp. 151-16.