Article(id=1240655134238232856, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2025.03.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720454400000, receivedDateStr=2024-07-09, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773724834260, onlineDateStr=2026-03-17, pubDate=1758729600000, pubDateStr=2025-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773724834260, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773724834260, creator=13701087609, updateTime=1773724834260, updator=13701087609, issue=Issue{id=1240655131507740845, tenantId=1146029695717560320, journalId=1240618002186551303, year='2025', volume='48', issue='3', pageStart='1', pageEnd='184', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773724833608, creator=13701087609, updateTime=1773725188865, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240656621609742880, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240656621613937185, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=57, endPage=64, ext={EN=ArticleExt(id=1240655134502474024, articleId=1240655134238232856, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Maritime traffic route extraction based on ship behavior pattern, columnId=1240655017900823355, journalTitle=Navigation of China, columnName=Marine Traffic Safety, runingTitle=null, highlight=null, articleAbstract=

Reasonable maritime route planning contributes to enhancing both the safety and economic efficiency of ship navigation. To address the challenges associated with route planning in complex waters, this paper proposes a method for extracting maritime traffic routes based on ship behavior patterns. Using Automatic Identification System (AIS) data, characteristic points of ship behavior patterns are identified through threshold judgment and a sliding window approach. A clustering algorithm is then applied to determine centroid points within each cluster, which represent the distribution of point sets. Finally, connection rules are established to sequentially link these centroids, thereby generating maritime traffic routes. Experimental analysis was conducted using AIS data from the Beibu Gulf waters. The results indicate that the routes extracted by this method align closely with the recommended routes published in the Navigation Guide for Ships in the Guangxi Area of the Beibu Gulf.

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为解决复杂水域内船舶航线规划困难的问题，提出一种基于船舶行为模式的海上交通航线提取方法。基于船舶自动识别系统（AIS）数据，使用阈值判断法与滑动窗口方法识别船舶行为模式特征点；运用聚类算法，对每一类聚类结果中的质心点进行搜索以表征点集的分布位置；制定连接规则依次连接质心点，生成海上交通航线；选取北部湾水域AIS数据进行试验分析。结果表明：该方法提取的航线与《北部湾广西海域船舶航行指南》中公布的推荐航路具有较好的相符性。

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