期刊文献+

基于历史航次信息的船舶典型轨迹 被引量:2

Method for Extracting Typical Ship Track According to Historical Navigation Data
下载PDF
导出
摘要 为提高船舶导航系统对航行经验的感知能力、学习能力和自适应能力,进而提高导航系统的实用性和可靠性。根据海上交通工程理论,建立船舶运动轨迹模型,并通过引入用于评估轨迹特征的轨迹参数,构建基于遗传算法(Genetic Algorithm,GA)的船舶典型轨迹适应度函数,提出从历史航次信息中获取有向的船舶运动的典型轨迹的方法。以运用上海—深圳航线为实例,通过GA,从相应历史航次信息中获取船舶从上海—深圳的典型轨迹,结果表明:该典型轨迹的获取方法具备一定的准确性。 Ship motion model is constructed according to the theory of marine traffic engineering and feature parameters of ship track are defined.The fitness function for typical ship track is constructed based on GA(Genetic Algorithm).The method for extract typical ship track from historical navigation data is devised.The method is verified through processing actual data of Shanghai-Shenzhen line.
作者 张进峰 朱学秀 彭斯杨 ZHANG Jinfeng;ZHU Xuexiu;PENG Siyang(School of Navigation,Wuhan University of Technology;National Engineering Research Center for Water Transport Safety,Wuhan University of Technology;Hubei Inland Shipping Technology Key Laboratory,Wuhan University of Technology,Wuhan 430063,China)
出处 《中国航海》 CSCD 北大核心 2021年第3期39-43,50,共6页 Navigation of China
基金 国家重点研发计划(2018YFC1407404)
关键词 船舶 历史航次信息 轨迹建模 遗传算法 典型轨迹 ship historical navigation data ship track model GA typical ship track
  • 相关文献

参考文献12

二级参考文献112

  • 1王家耀,魏海平,成毅,熊自明.时空GIS的研究与进展[J].海洋测绘,2004,24(5):1-4. 被引量:67
  • 2白莉媛,胡声艳,刘素华.一种基于模拟退火和遗传算法的模糊聚类方法[J].计算机工程与应用,2005,41(9):56-58. 被引量:11
  • 3侯惠芳,刘素华.一种改进的基于遗传算法的模糊C-均值算法[J].计算机工程,2005,31(17):152-154. 被引量:9
  • 4陈继东,孟小峰,赖彩凤.基于道路网络的对象聚类[J].软件学报,2007,18(2):332-344. 被引量:29
  • 5国际海事组织.通用船载自动识别系统国际标准汇编[G].袁安存,张淑芳编译.大连:大连海事大学出版社,2005.
  • 6LEE J G, HAN J W, WHANG K Y. Trajectory clustering: a partition-and-group framework[A]. Proceedings of the 2007 ACM SIG-MOD International Conference on Management of Data[C]. Beijing, China, 2007. 593-604.
  • 7CHANG C, ZHOU B Y. MuM-granularity visualization of trajectory clusters using sub-trajectory clustering[A]. Proceedings of the 7th IEEE International Conference on Data Mining Workshops[C]. Miami, Florida, USA, 2009. 577-582.
  • 8KREVELD M V, LUO J. The definition and computation of trajectory and sub-trajectory similarity[A]. Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems[C]. Seattle, Washington, USA. 2007. 324-327.
  • 9PELEKIS N, KOPANAKIS I, MARKETOS G, et al. Similarity search in trajectory databases[A]. Proceedings of the 14th International Symposium on Temporal Representation and Reasoning[C]. Washington, DC, USA, 2007. 129-140.
  • 10MICHAIL V, MARIOS H, DIMITRIOS G Indexing multidimensional time-series[J]. The International Journal on Very Large Data Bases, 2006, 15(1): 1-20.

共引文献231

同被引文献18

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部