摘要
人为和组织因素是导致船舶碰撞的主要原因,目前的风险评估模型没有充分考虑人为和组织因素的影响。为此,调查200起船舶碰撞事故,基于人为因素分析和分类系统提出改进的船舶碰撞事故人为和组织因素调查框架。采用关联规则算法(Apriori)对各风险因素开展关联分析,结合解释结构模型构建贝叶斯风险评估模型,提出一种基于数据挖掘的贝叶斯量化方法。针对船舶碰撞破损进水风险开展研究,确定导致事故风险的关键因素和致因链。结果表明,所提出的方法能够识别船舶碰撞破损进水事故的潜在原因,可用于船舶碰撞破损进水的风险预测,有助于降低事故风险。
Human and organizational factors(HOFS)are major contributors to ship collisions.However,current risk assessment models often fail to adequately address their impact.To address this gap,this study investigated 200 ship collision accidents and proposed an improved framework(HFACS-SCA)(Ship Collision Accident)for investigating HOFS in ship collisions based on the Human Factors Analysis and Classification System.Apriori association rules were applied to conduct an association analysis of each risk factor,and a Bayesian(BN)risk assessment model was constructed by integrating the ISM explanatory structure model.This study also introduced a BN quantification method based on data mining.The risk of ship collision breakage and water ingress was analyzed,and key factors and causal chains leading to accident risk were identified.The results show that the proposed method can effectively identify the potential causes of ship collision damage and water ingress accidents and can be used for risk prediction in such accidents,thereby contributing to the reduction of accident risks.
作者
郭明阳
陈淼
吕佳
袁利毫
李欣未
张志辉
GUO Mingyang;CHEN Miao;LYU Jia;YUAN Lihao;LI Xinwei;ZHANG Zhihui(College of Shipbuilding Engineering,Harbin Engineering University,Harbin 150001,China;Yantai Research Institute,Harbin Engineering University,Yantai 264000,China)
出处
《哈尔滨工程大学学报》
北大核心
2025年第9期1693-1700,共8页
Journal of Harbin Engineering University
基金
国家自然科学基金项目(51509060).
