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Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China

机译：水运交通事故严重程度的贝叶斯网络建模与分析：以中国为例

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摘要

The rapid development of the shipping industry requires the use of large vessels carrying high-volume cargoes. Accidents incurred by these vessels can lead to a heavy loss of life and damage to the environment and property. As a leading country in international trade, China has developed its waterway transport systems, including inland waterways and coastal shipping, in the past decades. A few catastrophic shipping accidents have occurred during this period. This paper aims to develop a new risk analysis approach based on Bayesian networks (BNs) to enable the analysis of accident severity in waterborne transportation. Although the risk data are derived from accidents that occurred in China's waters, the risk factors influencing accident severity and the risk modelling methodology are generic and capable of generating useful insights on waterway risk analysis in a broad sense.
机译：航运业的飞速发展要求使用运载大量货物的大型船舶。这些船只发生的事故可导致严重的生命损失，并破坏环境和财产。作为国际贸易的领先国家，中国在过去几十年中发展了其水路运输系统，包括内陆水路和沿海航运。在此期间发生了几起灾难性的运输事故。本文旨在开发一种新的基于贝叶斯网络（BNs）的风险分析方法，以分析水运中的事故严重性。尽管风险数据来自中国水域发生的事故，但影响事故严重性的风险因素和风险建模方法却是通用的，能够从广义上对水路风险分析产生有用的见解。

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