[1]刘磊,蒋仲廉,初秀民,等.船舶自动识别系统数据修复和预测算法研究[J].哈尔滨工程大学学报,2019,40(06):1072-1077.[doi:10.11990/jheu.201803011]
 LIU Lei,JIANG Zhonglian,CHU Xiumin,et al.Automatic identification system data restoration and prediction[J].hebgcdxxb,2019,40(06):1072-1077.[doi:10.11990/jheu.201803011]
点击复制

船舶自动识别系统数据修复和预测算法研究(/HTML)
分享到:

《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2019年06期
页码:
1072-1077
栏目:
出版日期:
2019-06-05

文章信息/Info

Title:
Automatic identification system data restoration and prediction
作者:
刘磊12 蒋仲廉12 初秀民12 钟诚12 张代勇13
1. 武汉理工大学 国家水运安全工程技术研究中心, 湖北 武汉 430063;
2. 武汉理工大学 能源与动力工程学院, 湖北 武汉 430063;
3. 武汉理工大学 物流工程学院, 湖北 武汉 430063
Author(s):
LIU Lei12 JIANG Zhonglian12 CHU Xiumin12 ZHONG Cheng12 ZHANG Daiyong13
1. National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China;
2. School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China;
3. School of Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
关键词:
水路运输数据修复和预测BP神经网络分段三次Hermite插值三次样条插值联合数学模型自动识别系统数据修复和预测精度
分类号:
U675.7
DOI:
10.11990/jheu.201803011
文献标志码:
A
摘要:
针对船舶AIS数据丢失或错误等问题,本文借助分段三次Hermite插值实现AIS数据初步修复或预测,建立神经网络训练集和测试集,开展单点和连续多点AIS数据修复和预测;对比分析了BP神经网络与三次样条插值、分段三次Hermite插值方法以及组合算法在船舶AIS数据修复和预测中的精度。以重庆弯曲河段和武汉顺直河段为例,分析了航道平面形态、算法组合等对于船舶AIS数据修复和预测精度的影响。结果表明:联合算法有效提升了船舶AIS数据修复精度;在船舶AIS预测中,神经网络模型表现最优。研究成果可为船舶行为特征分析、建模等相关领域的研究提供借鉴。

参考文献/References:

[1] 邹秋花. 基于模糊综合函数的AIS与雷达信息融合研究[D]. 大连:大连海事大学, 2013.ZOU Qiuhua. Study on AIS and radar information fusion based on fuzzy comprehensive function[D]. Dalian:Dalian Maritime University, 2013.
[2] 于俊逸, 陈伟, 刘建, 等. 内河航道VTS与AIS系统信息融合关键技术的研究[C]//第十三届海峡两岸智能运输系统学术研讨会论文集. 成都, 2013.YU Junyi, CHEN Wei, LIU Jian, et al. Research on VTS and AIS information fusion in the inland waterway[C]//The Taiwan Strait intelligent transportation systems Symposium. Chengdu, 2013.
[3] 林祎珣. 数据挖掘技术在海上交通特征分析中的应用研究[D]. 厦门:集美大学, 2011.LIN Yixun. Application of data mining technology in analysis of marine traffic characteristics[D]. Xiamen:JiMei University, 2011.
[4] 吴青, 崔建平, 马枫, 等. 基于奥村模型的内河AIS基站监测范围研究[J]. 武汉理工大学学报(信息与管理工程版), 2011, 33(1):36-39, 42.WU Qing, CUI Jianping, MA Feng, et al. Research of monitoring scope of inland ais base station based on Okumura-Hata model[J]. Journal of Wuhan University of Technology (information & management engineering), 2011, 33(1):36-39, 42.
[5] 魏冰. AIS的应用及前景展望[J]. 中国水运, 2012, 12(7):70, 92.WEI Bing. AIS application and prospects[J]. China water transport, 2012, 12(7):70, 92.
[6] 童笑. 基于AIS的电子海图导航系统设计与实现[D]. 武汉:武汉理工大学, 2012.TONG Xiao. The design and implementation of electronic chart navigation system based on AIS[D]. Wuhan:Wuhan University of Technology, 2012.
[7] WANG Yang, ZHANG Jinfen, CHEN Xianqiao, et al. A spatial-temporal forensic analysis for inland-water ship collisions using AIS data[J]. Safety science, 2013, 57:187-202.
[8] FIORINI M, CAPATA A, BLOISI D D. AIS data visualization for maritime spatial planning (MSP)[J]. International journal of e-navigation and maritime economy, 2016, 5:45-60.
[9] 刘兴龙, 初秀民, 马枫, 等. 山区航道虚拟航标基站布设间距研究[J]. 哈尔滨工程大学学报, 2016, 37(3):382-387.LIU Xinglong, CHU Xiumin, MA Feng, et al. Base station spacing of virtual aids to navigation in mountain waterways[J]. Journal of Harbin Engineering University, 2016, 37(3):382-387.
[10] 戴鹏睿. AIS轨迹动态插值在实时视景显示中的应用[J]. 电子设计工程, 2016, 24(14):172-175.DAI Pengrui. Application of AIS trajectory dynamic interpolation in real-time visual display[J]. Electronic design engineering, 2016, 24(14):172-175.
[11] 吴建华, 吴琛, 刘文, 等. 舶舶AIS轨迹异常的自动检测与修复算法[J]. 中国航海, 2017, 40(1):8-12, 101.WU Jianhua, WU Chen, LIU Wen, et al. Automatic detection and restoration algorithm for trajectory anomalies of ship AIS[J]. Navigation of China, 2017, 40(1):8-12, 101.
[12] 刘立群, 吴超仲, 褚端峰, 等. 基于Vondrak滤波和三次样条插值的船舶轨迹修复研究[J]. 交通信息与安全, 2015, 33(4):100-105.LIU Liqun, WU Chaozhong, CHU Duanfeng, et al. A study of ship trajectory restoration based on Vondrak filtering and cubic spline interpolation[J]. Journal of transport information and safety, 2015, 33(4):100-105.
[13] NGUYEN V S, IM N K, LEE S M. The interpolation method for the missing AIS data of ship[J]. Journal of navigation and port research, 2015, 39(5):377-384.
[14] 姚志洪, 蒋阳升, 韩鹏, 等. 基于神经网络的小时间粒度交通流预测模型[J]. 交通运输系统工程与信息, 2017, 17(1):67-73.YAO Zhihong, JIANG Yangsheng, HAN Peng, et al. Traffic flow prediction model based on neural network in small time granularity[J]. Journal of transportation systems engineering and information technology, 2017, 17(1):67-73.
[15] 徐婷婷, 柳晓鸣, 杨鑫. 基于BP神经网络的船舶航迹实时预测[J]. 大连海事大学学报, 2012, 38(1):9-11.XU Tingting, LIU Xiaoming, YANG Xin. BP neural network-based ship track real-time prediction[J]. Journal of Dalian Maritime University, 2012, 38(1):9-11.
[16] 甄荣, 金永兴, 胡勤友, 等. 基于AIS信息和BP神经网络的船舶航行行为预测[J]. 中国航海, 2017, 40(2):6-10.ZHEN Rong, JIN Yongxing, HU Qinyou, et al. Vessel behavior prediction based on AIS data and BP neural network[J]. Navigation of China, 2017, 40(2):6-10.
[17] 戴吾蛟, 丁晓利, 朱建军. 基于观测值质量指标的GPS观测量随机模型分析[J]. 武汉大学学报(信息科学版), 2008, 33(7):718-722.DAI Wujiao, DING Xiaoli, ZHU Jianjun. Comparing GPS stochastic models based on observation quality indices[J]. Geomatics and Information Science of Wuhan University, 2008, 33(7):718-722.
[18] GLOROT X, BENGIO Y. Understanding the difficulty of training deep feedforward neural networks[J]. Journal of machine learning research, 2010, 9:249-256.

相似文献/References:

[1]郭威治,刘敬贤,刘文,等.受限水域超大型船舶富裕水深定量计算研究[J].哈尔滨工程大学学报,2018,39(09):1491.[doi:10.11990/jheu.201712006]
 GUO Weizhi,LIU Jingxian,LIU Wen,et al.Quantitative study on under-keel clearance for ultra large-scale ships in restricted waterways[J].hebgcdxxb,2018,39(06):1491.[doi:10.11990/jheu.201712006]
[2]赵艺为,张培林,陈沿伊.长江航道承载力影响因素体系构建[J].哈尔滨工程大学学报,2018,39(09):1498.[doi:10.11990/jheu.201712038]
 ZHAO Yiwei,ZHANG Peilin,CHEN Yanyi.Influencing factor system of the Yangtze waterway carrying capacity[J].hebgcdxxb,2018,39(06):1498.[doi:10.11990/jheu.201712038]
[3]李佳,初秀民,刘兴龙,等.内河船舶缺失轨迹修复方法[J].哈尔滨工程大学学报,2019,40(01):67.[doi:10.11990/jheu.201708038]
 LI Jia,CHU Xiumin,LIU Xinglong,et al.An approach for restoring the lost trajectories of vessels in inland waterways[J].hebgcdxxb,2019,40(06):67.[doi:10.11990/jheu.201708038]

备注/Memo

备注/Memo:
收稿日期:2018-03-05。
基金项目:国家自然科学基金项目(51479155,51709220);中央高校基本科研业务经费专项资金(2017-zy-0479).
作者简介:刘磊,男,博士研究生;蒋仲廉,男,副研究员.
通讯作者:蒋仲廉,E-mail:z.jiang@whut.edu.cn.
更新日期/Last Update: 2019-06-03