2026-04-17T22:26:38Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4051582026-01-14T07:48:56Zcom_2072_1033col_2072_452950

Identification of risk influential factors for fishing vessel accidents using claims data from fishery mutual insurance association Wang, Fang Du, Weijie Feng, Hongxiang Ye, Yun Grifoll Colls, Manel Liu, Guiyun Zheng, Pengjun Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental Universitat Politècnica de Catalunya. BIT - Barcelona Innovative Transportation Àrees temàtiques de la UPC::Nàutica::Seguretat marítima::Accidents marítims Àrees temàtiques de la UPC::Enginyeria agroalimentària::Pesca::Pesca marina Fishing boats--Accidents Fishers--Accidents Employers’ liability insurance Fishing vessel Accident analysis Random forest Bayesian network Feature selection Embarcacions de pesca--Accidents Pescadors--Accidents Assegurances d'accidents de treball This research aims to identify and analyze the significant risk factors contributing to accidents involving fishing vessels, a crucial step towards enhancing safety and promoting sustainable practices in the fishing industry. Using a data-driven Bayesian network (BN) model that incorporates feature selection through the random forest (RF) method, we explore these key factors and their interconnected relationships. A review of past academic studies and accident investigation reports from the Fishery Mutual Insurance Association (FMIA) revealed 17 such factors. We then used the random forest model to rank these factors by importance, selecting 11 critical ones to build the Bayesian network model. The data-driven Bayesian network (BN) model is further utilized to delve deeper into the central factors influencing fishing vessel accidents. Upon validation, the study results show that incorporating the random forest feature selection method enhances the simplicity, reliability, and precision of the BN model. This finding is supported by a thorough performance evaluation and scenario analysis. Postprint (published version) 2023-09-07 Article Wang, F. [et al.]. Identification of risk influential factors for fishing vessel accidents using claims data from fishery mutual insurance association. "Sustainability (Switzerland)", 7 Setembre 2023, vol. 15, núm. 18. 2071-1050 https://hdl.handle.net/2117/405158 10.3390/su151813427 eng https://www.mdpi.com/2071-1050/15/18/13427 http://creativecommons.org/licenses/by/4.0/ Open Access Attribution 4.0 International application/pdf Multidisciplinary Digital Publishing Institute (MDPI)