Article(id=1263533688185340277, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2026.02.004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741708800000, receivedDateStr=2025-03-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1779179506583, onlineDateStr=2026-05-19, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1779179506583, onlineIssueDateStr=2026-05-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1779179506583, creator=13701087609, updateTime=1779179506583, updator=13701087609, issue=Issue{id=1263533678655881533, tenantId=1146029695717560320, journalId=1240618002186551303, year='2026', volume='49', issue='2', pageStart='1', pageEnd='163', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1779179504312, creator=13701087609, updateTime=1779179563167, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1263533925629047616, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1263533925629047617, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=34, endPage=41, ext={EN=ArticleExt(id=1263533690215383432, articleId=1263533688185340277, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Analysis of the impact of tropical cyclones on shipping routes in the Western Pacific based on a clustering method, columnId=1240655017900823355, journalTitle=Navigation of China, columnName=Marine Traffic Safety, runingTitle=null, highlight=null, articleAbstract=

To enhance the safety and efficiency of maritime route planning, this study proposes a hybrid clustering method integrating multiple algorithms to evaluate the impact of tropical cyclones in the Western Pacific. Firstly, using tropical cyclone data from the National Oceanic and Atmospheric Administration (NOAA), we characterize genesis patterns, intensity variations, and track features of tropical cyclones from 1924 to 2023. Secondly, the K-means clustering algorithm is employed to analyze spatiotemporal distribution, movement speed and direction, while a Gaussian Mixture Model（GMM）is used to identify hotspot regions and high-frequency activity belts. Finally, to overcome the limitations of two-dimensional clustering, we propose a hybrid clustering approach combining 2D and 3D clustering analyses. By overlaying tropical cyclone tracks with major shipping routes, we reveal their potential impacts on maritime safety. Experimental results demonstrate that tropical cyclones primarily affect latitudes between 10°N and 25°N, with seasonal variations:cyclones are generally weaker and more localized in winter-spring, whereas typhoons are stronger and more frequent in summer-autumn. In terms of movement direction, low-latitude cyclones initially move westward from east and then recurve northward near 15°N, while high-latitude cyclones move westward before turning northeastward. The hybrid clustering method effectively identifies tropical cyclone risk zones, providing critical references for shipping route planning and risk management.

, correspAuthors=Shenping Hu, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Yu Wang, Shengjun Wang, Shenping Hu, Xinda He, Xiangqian Meng), CN=ArticleExt(id=1263533691624669586, articleId=1263533688185340277, tenantId=1146029695717560320, journalId=1240618002186551303, language=CN, title=基于聚类算法的热带气旋对西太平洋航路的影响分析, columnId=1240655018068595518, journalTitle=中国航海, columnName=海上交通安全, runingTitle=null, highlight=null, articleAbstract=

为提升航运规划的安全性及效率，文章提出了基于多聚类算法融合的西太平洋热带气旋影响分析方法。首先，基于美国国家海洋和大气管理局（NOAA）提供的热带气旋数据，得出1924—2023年热带气旋的生成规律、强度变化和移动路径等特征；其次采用K-means聚类算法分析热带气旋的时空分布、移动速度及方向，运用高斯混合聚类算法分析热带气旋的热点区域、高频活动带；最后考虑二维聚类的局限性，提出基于二维与三维聚类的混合聚类分析方法，并将热带气旋轨迹与主要航线进行叠加分析，揭示其对航线安全的潜在影响。结果表明，热带气旋主要影响10°N至25°N，且存在季节差异，其中冬春气旋弱且范围小，夏秋台风强且频繁。在气旋的移动方向上，低纬度气旋自东向西，接近15°N时先向西再北折，高纬度气旋则西行后转向东北。基于混合聚类方法能够有效识别热带气旋的风险区域，为航运规划与风险管理提供参考。

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王宇（1971—），男，高级船长，研究方向为载运工具运用工程、航海技术。

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王宇（1971—），男，高级船长，研究方向为载运工具运用工程、航海技术。

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