Prediction of 3-D Ocean Temperature Based on Self-Attention and Predictive RNN

doi:10.1109/LGRS.2024.3358348

IOCAS-IR > 海洋环流与波动重点实验室

	Prediction of 3-D Ocean Temperature Based on Self-Attention and Predictive RNN
	Yue, Weihao 1; Xu, Yongsheng2,3,4 ; Xiang, Liang 2,4,5; Zhu, Shanliang 6; Huang, Chao2,5 ; Zhang, Qingjun 6; Zhang, Liqiang ; Zhan, Xiangguang 1
	2024
发表期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN	1545-598X
卷号	21 页码:5
通讯作者	Yue, Weihao(2021090023@mails.qust.edu.cn)
摘要	Predicting the 3-D ocean temperature field is a significant task that helps to understand global climate change and the state of ocean motion. Lots of numerical and data-driven models are used to predict ocean temperatures. However, these methods are restricted to the time-sequence prediction of discrete points or rely on convolutional layers to inefficiently capture local spatial dependencies for spatio-temporal prediction. In this letter, we propose a deep learning model named self-attention predictive recurrent neural network (SA-PredRNN) that combines attention mechanisms and predictive recurrent neural networks to capture global positional correlations and spatio-temporal features. Global gridded Argo temperature data with Barnes objective analysis (BOA-ARGO) are used to predict the future 3-D ocean temperature. The average root mean square errors (RMSEs) of the proposed model are promoted by at most 11% and 10%, which indicates that the SA-PredRNN model has a better performance than the other baseline models.
关键词	Climate change Recurrent neural networks Temperature measurement Ocean temperature Predictive models Global gridded temperature data with Barnes objective analysis (BOA-ARGO) predictive recurrent neural network (PredRNN) self-attention
DOI	10.1109/LGRS.2024.3358348
收录类别	SCI
语种	英语
资助项目	Laoshan Laboratory Science and Technology Innovation Projects
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001173361400015
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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.qdio.ac.cn/handle/337002/184811
专题	海洋环流与波动重点实验室
通讯作者	Yue, Weihao
作者单位	1.Chinese Acad Sci, Inst Oceanol, Lab Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China 3.Laoshan Lab, Lab Ocean & Climate Dynam, Qingdao 266228, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100039, Peoples R China 5.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Peoples R China 6.China Acad Space Technol, Inst Remote Sensing Satellite, Beijing 100094, Peoples R China
第一作者单位	中国科学院海洋研究所
通讯作者单位	中国科学院海洋研究所
推荐引用方式 GB/T 7714	Yue, Weihao,Xu, Yongsheng,Xiang, Liang,et al. Prediction of 3-D Ocean Temperature Based on Self-Attention and Predictive RNN[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2024,21:5.
APA	Yue, Weihao.,Xu, Yongsheng.,Xiang, Liang.,Zhu, Shanliang.,Huang, Chao.,...&Zhan, Xiangguang.(2024).Prediction of 3-D Ocean Temperature Based on Self-Attention and Predictive RNN.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,21,5.
MLA	Yue, Weihao,et al."Prediction of 3-D Ocean Temperature Based on Self-Attention and Predictive RNN".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 21(2024):5.