Analysis of fishing vessel accidents with Bayesian network and Chi-square methods


Ugurlu F., YILDIZ S., BORAN M., Ugurlu O., Wang J.

OCEAN ENGINEERING, vol.198, 2020 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 198
  • Publication Date: 2020
  • Doi Number: 10.1016/j.oceaneng.2020.106956
  • Journal Name: OCEAN ENGINEERING
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Compendex, Computer & Applied Sciences, Environment Index, Geobase, ICONDA Bibliographic, INSPEC, Metadex, Civil Engineering Abstracts

Abstract

Commercial fishing is an important industry that generates income directly or indirectly to many people in the world. It is impossible to carry out a fishing activity on this scale without a vessel. Therefore, fishing vessels are the most important element of modern fishing industry. Fishing vessels play a key role in fishing, transporting and storing fish. Thousands of people die every year as a result of fishing vessel accidents. In order to carry out sustainable fishing operations, fishing vessel accidents should be investigated and measures should be taken to prevent them. Therefore, in this study for analysing of accidents occurred between 2008 and 2018 in fishing vessels, with full lengths of 7 m and above, Bayesian network, chi-square methods were used. As a result, recommendations were made to prevent accidents. Also, Accident (Bayes) Network, which summarizes the occurrence of accidents on fishing vessels, is presented. These networks allow to understand the occurrence of accidents in fishing vessels and to estimate the occurrence of accidents in variable conditions. It was also found that there was a significant relationship between accident category and vessel length, vessel age, loss of life and loss of vessel.