基于特征优选和SVM的船舶航行事故致因分析  

An Analysis of Risk Factors of Maritime Navigation Accidents Based on Feature Optimization and SVM

作　　者：石荣丽 林艺舒 SHI Rongli;LIN Yishu(School of Medical Business,Guangdong Pharmaceutical University,Zhongshan 528000,China;Guangdong Research Base for Drug Regulatory Science,Zhongshan 528000,China;NMPA Key Laboratory for Technology Research and Evaluation of Pharmacovigilance,Zhongshan 528000,China;School of Internet Finance and Information Engineering,Guangdong University of Finance,Guangzhou 510521,China)

机构地区：[1]广东药科大学医药商学院,广东中山528000 [2]广东省药品监管科学研究基地,广东中山528000 [3]国家药品监督管理局药物警戒技术研究与评价重点实验室,广东中山528000 [4]广东金融学院互联网金融与信息工程学院,广东广州510521

出　　处：《运筹与管理》2023年第12期99-105,共7页Operations Research and Management Science

基　　金：国家社会科学基金资助项目(20BGL258)。

摘　　要：在“海运强国”战略和建设“海上丝绸之路”的大背景下,我国对船舶航行安全提出更高的要求。本文基于特征优选和支持向量机模型,挖掘出船舶航行事故的致因并分析各个因素对事故的影响程度。首先,通过文本挖掘和相关性分析对输入特征进行优选,筛选出航行事故责任船舶与其他船舶存在明显差异的因素作为航行事故致因。然后,构建基于SVM的船舶航行事故识别模型,并通过交叉验证及群体智能优化算法选择模型的最佳参数组合,得到最优的分类模型。最后,利用递归特征消除算法将上述致因对事故的影响程度进行排序和筛选,挖掘出事故的关键致因。通过广东省的水上交通事故实例验证模型的有效性,结果表明:本模型(正确度为90.1%)较传统单一的SVM模型(正确度为75.0%)具有更高的精度。研究结果可为减少船舶航行事故提供有效的科学建议。In the context of the national maritime power strategy and the Maritime Silk Road Initiative,vessels tend to be increasing in number and capacity.These factors have been combined to deteriorate the navigation environment and increase maritime navigation accidents.Due to the difficulty of search and rescue,these accidents can result in many casualties,huge economic losses and irreparable environmental damage.Therefore,it is crucial and timely to dig out risk factors of maritime navigation accidents.According to the literature review,the existing researches on risk factors of maritime navigation accidents have the following shortcomings:(1)There is a lack comprehensive and objective consideration of the risk factors,especially detailed analysis of human factors,although many studies have shown that human factors are very important to maritime navigation accidents.(2)Maritime navigation accidents are with low probability.Due to the lack of public data,the accident sample size cannot meet most of the research models.In order to meet the demand of sample size,existing studies mainly obtain large-size samples by expanding the research area and data expansion.However,different areas have different risk factors of maritime navigation accidents,and data expansion cannot fully reflect the characteristics of data.Therefore,both area expansion and data expansion are not conducive to excavating the risk factors of maritime navigation accidents accurately.(3)The existing model can not be used to predict the probability of accidents,or directly used to analyse the impact of each risk factor on the accidents.(4)The existing studies mainly dig out risk factors of maritime navigation accidents by analysing the data of the vessels involved in navigation accidents,or compare the data of vessels in a certain type of accidents with other types of accidents.In fact,the vessels involved in the accidents do not necessarily have the characteristics of risk.To solve the first problem,this paper digs out the risk factors of maritime navigat

关 键 词：交通安全 航行事故 致因因素 SVM-RFE 优化算法 

分 类 号：U698.6[交通运输工程—港口、海岸及近海工程]