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Time Series Prediction Methods for Depth-Averaged Current Velocities of Underwater Gliders
Zhou YJ(周耀鉴); Yu JC(俞建成); Wang XH(王晓辉)
作者部门海洋机器人卓越创新中心
关键词Underwater Glider Time Series Depth-averaged Current Velocities (Dacvs)
发表期刊IEEE ACCESS
ISSN2169-3536
2017
卷号5页码:5773-5384
收录类别SCI ; EI
EI收录号20173504088091
WOS记录号WOS:000401431300066
产权排序1
资助机构National Natural Science Foundation of China [61233013]
摘要In this paper, we propose time series prediction methods for depth-averaged current velocities (DACVs) of underwater gliders. Based on historical DACV data, these methods can predict the DACVs of future profiles with good performance. Regarding DACVs as time series, we use backpropagation neural network and least squares support vector machine (LSSVM) methods to predict the DACVs. To obtain better prediction performance, the features of DACVs are considered, and we use empirical mode decomposition (EMD) to decompose the time series into several sub-series. Then, the two methods are reused to predict each sub-series, and the results of all the sub-series with each method are added. Based on the real-time DACVs obtained from the simulation environment and the DACVs obtained from sea trials, we test and verify the four methods. The results demonstrate that all the methods exhibit a good prediction performance for conditions in which ocean currents are relatively regular; whereas in other cases, EMD-LSSVM shows inherent robustness and superiority compared with the other three methods.
语种英语
WOS标题词Science & Technology ; Technology
WOS类目Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
关键词[WOS]MONTEREY BAY
WOS研究方向Computer Science ; Engineering ; Telecommunications
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/20499
专题海洋机器人卓越创新中心
通讯作者Yu JC(俞建成)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
推荐引用方式
GB/T 7714
Zhou YJ,Yu JC,Wang XH. Time Series Prediction Methods for Depth-Averaged Current Velocities of Underwater Gliders[J]. IEEE ACCESS,2017,5:5773-5384.
APA Zhou YJ,Yu JC,&Wang XH.(2017).Time Series Prediction Methods for Depth-Averaged Current Velocities of Underwater Gliders.IEEE ACCESS,5,5773-5384.
MLA Zhou YJ,et al."Time Series Prediction Methods for Depth-Averaged Current Velocities of Underwater Gliders".IEEE ACCESS 5(2017):5773-5384.
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