IOCAS-IR  > 海洋环流与波动重点实验室
A Machine-Learning Model for Forecasting Internal Wave Propagation in the Andaman Sea
Zhang, Xudong1,2; Li, Xiaofeng1,2; Zheng, Quanan1,2
2021
Source PublicationIEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
Volume14Pages:3095-3106
Corresponding AuthorLi, Xiaofeng(xiaofeng.li@ieee.org)
AbstractInternal waves (IWs) are broadly distributed globally and have significant impacts on offshore engineering and underwater navigation. The prediction of IW propagation is a challenging task because of the complex factors involved. In this study, a machine-learning model was developed to predict IW propagation in the Andaman Sea. The model is based on a back-propagation neural network trained by 1189 IW samples, including the crest length and the peak-to-peak distance of IWs, extracted from 123 Moderate-Resolution Imaging Spectroradiometer (MODIS) images and 33 Ocean Land Color Instrument (OLCI) images acquired from 2015 to 2019 and corresponding ocean environment parameters. Using the leading wave crest within an IW packet as input, we ran the model to forecast the IW locations and compare them with satellite observations. The average root-mean-square difference between the model-forecasted and satellite-observed IW leading crest after one tidal cycle was 3.21 km. The corresponding averaged correlation coefficient was 0.95 and the average Frechet Distance was 11.46 km. We reiterated the model run over two tidal periods and obtained similar statistical results, indicating the robustness of forecasting IW packets. We find that reducing the time step helped to improve forecasting accuracy. The influence of input errors and seasonal variations on model results are discussed and an analysis shows that the initial propagation direction introduced to the model is necessary for cross-propagating IW patterns. Comparisons with the Korteweg-de Vries equation results show that the developed model has better performance and is more robust.
KeywordPredictive models Training Satellites Machine learning Oceans MODIS Data models Andaman sea internal wave (IW) forecast machine learning
DOI10.1109/JSTARS.2021.3063529
Indexed BySCI
Language英语
Funding ProjectStrategic Priority Research Program of the Chinese Academy of Sciences[XDA19090103] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19060101] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB42000000] ; National Natural Science Foundation for Young Scientists of China[41906157] ; National Natural Science Foundation for Young Scientists of China[41604200] ; National Natural Science Foundation of China[41776183] ; Major Scientific, and Technological Innovation Projects in Shandong Province[2019JZZY010102] ; Key Project of Center for Ocean Mega-Science, Chinese Academy of Sciences[COMS2019R02] ; CAS Program[Y9KY04101 L]
WOS Research AreaEngineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEngineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000634496000002
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.qdio.ac.cn/handle/337002/170291
Collection海洋环流与波动重点实验室
Corresponding AuthorLi, Xiaofeng
Affiliation1.Chinese Acad Sci, CAS Key Lab Ocean Circulat & Waves, Inst Oceanol, Qingdao 266071, Peoples R China
2.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China
First Author AffilicationInstitute of Oceanology, Chinese Academy of Sciences;  Center for Ocean Mega-Science, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Oceanology, Chinese Academy of Sciences;  Center for Ocean Mega-Science, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Xudong,Li, Xiaofeng,Zheng, Quanan. A Machine-Learning Model for Forecasting Internal Wave Propagation in the Andaman Sea[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2021,14:3095-3106.
APA Zhang, Xudong,Li, Xiaofeng,&Zheng, Quanan.(2021).A Machine-Learning Model for Forecasting Internal Wave Propagation in the Andaman Sea.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,14,3095-3106.
MLA Zhang, Xudong,et al."A Machine-Learning Model for Forecasting Internal Wave Propagation in the Andaman Sea".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 14(2021):3095-3106.
Files in This Item:
File Name/Size DocType Version Access License
09368983.pdf(6735KB)期刊论文出版稿延迟开放CC BY-NC-SAView 2023-7-1后可获取
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhang, Xudong]'s Articles
[Li, Xiaofeng]'s Articles
[Zheng, Quanan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhang, Xudong]'s Articles
[Li, Xiaofeng]'s Articles
[Zheng, Quanan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhang, Xudong]'s Articles
[Li, Xiaofeng]'s Articles
[Zheng, Quanan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 09368983.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.