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Compared with ocean transportation, inland waterway transportation (IWT) has issues such as a low configuration standard of navigation equipment, insufficient crew knowledge and skills, and the relatively more complex hydrographic environment of inland waterways. To recognize and quantify the risk of IWT, this study proposes a novel risk assessment method. Firstly, text mining by Python is applied to recognize the risk influential factors (RIFs) from marine accident investigation reports (MAIRs), and a risk evaluation hierarchy system is established. Secondly, a risk assessment model which integrates failure mode and effects analysis (FMEA), a belief rule-based Bayesian network (BRBN) and evidential reasoning (ER) is proposed to quantify the risk level of influential factors. Finally, a case study of the Songhua River was carried out to verify the feasibility and practicality of the established risk evaluation index system and research methods. The targeted preventive measures are proposed to improve the safety of IWT. This study shows that misobservation and poor safety awareness are the most important human factors affecting the safety of IWT, whereas the organizational factors have relatively low risk priority. It is suggested that stakeholders should strengthen the assessment of crew members and improve their ability to recognize hazards.
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Xia et al. (2023) studied this question.
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