Ocean Temperature Prediction Based on Stereo Spatial and Temporal 4-D Convolution Model | |
Zuo XY(左心怡)2,3,4,5; Zhou XF(周晓锋)2,3,4; Guo DQ(郭大权)2,3,4; Li S(李帅)2,3,4,5; Liu SR(刘舒锐)2,3,4; Xu CH(徐春晖)1,4 | |
刊名 | IEEE Geoscience and Remote Sensing Letters |
2022 | |
卷号 | 19页码:1-5 |
关键词 | Convolution Dual characteristics Ocean temperature ocean temperature prediction Predictive models Robots Sea surface Solid modeling stereo spatial and temporal 4-D convolution model (SST-4D-CNN). Temperature distribution |
ISSN号 | 1545-598X |
产权排序 | 1 |
英文摘要 | Ocean temperature prediction has always occupied an important position in the research of ocean-related fields. The current studies are mostly based on the temperature of the sea surface, but the prediction of ocean internal temperature is more important in practical applications. At present, most of the research studies on the prediction of ocean internal temperature are based on time series, few of which consider the dual characteristics of time and space. Therefore, the accuracy is insufficient, especially for the prediction of thermocline and deep-sea locations. This letter proposes the stereo spatial and temporal 4-D convolution model (SST-4D-CNN) to predict the temperature in the ocean, which fully considers the dual characteristics of time series and oceanic spatial relationship to improve the prediction accuracy. The model includes 4-D convolution module, residual module and recalibration module to predict the horizontal and profile temperature changes from the sea surface to 2000-m underwater. In this letter, the prediction experiment is carried out using the real-time analysis data-temperature dataset from National Marine Data Center. The results show that the accuracy of this method in horizontal and profile prediction is above 98.02%, and most of them are more than 99%. IEEE |
资助项目 | National Key Research and Development Program of China[2018YFC0308205] |
WOS关键词 | SEA-SURFACE TEMPERATURE |
WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
语种 | 英语 |
WOS记录号 | WOS:000730789400075 |
资助机构 | National Key Research and Development Program of China under Grant 2018YFC0308205 |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/29501] |
专题 | 沈阳自动化研究所_数字工厂研究室 |
通讯作者 | Zhou XF(周晓锋) |
作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 5.School of Computer Science, University of Chinese Academy of Sciences, Beijing 100049, China |
推荐引用方式 GB/T 7714 | Zuo XY,Zhou XF,Guo DQ,et al. Ocean Temperature Prediction Based on Stereo Spatial and Temporal 4-D Convolution Model[J]. IEEE Geoscience and Remote Sensing Letters,2022,19:1-5. |
APA | Zuo XY,Zhou XF,Guo DQ,Li S,Liu SR,&Xu CH.(2022).Ocean Temperature Prediction Based on Stereo Spatial and Temporal 4-D Convolution Model.IEEE Geoscience and Remote Sensing Letters,19,1-5. |
MLA | Zuo XY,et al."Ocean Temperature Prediction Based on Stereo Spatial and Temporal 4-D Convolution Model".IEEE Geoscience and Remote Sensing Letters 19(2022):1-5. |
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