Prediction of Significant Wave Height in Offshore China Based on the Machine Learning Method
文献类型：期刊论文
| 作者 | Feng, Zhijie4; Hu, Po1,2,3 ; Li, Shuiqing1,2,3; Mo, Dongxue2,3
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| 刊名 | JOURNAL OF MARINE SCIENCE AND ENGINEERING
 |
| 出版日期 | 2022-06-01 |
| 卷号 | 10期号:6页码:20 |
| 关键词 | wave height recurrent neural network long short-term memory network GRU EMD |
| DOI | 10.3390/jmse10060836 |
| 通讯作者 | Hu, Po(hupo@qdio.ac.cn) |
| 英文摘要 | Accurate wave prediction can help avoid disasters. In this study, the significant wave height (SWH) prediction performances of the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit network (GRU) were compared. The 10 m u-component of wind (U10), 10 m v-component of wind (V10), and SWH of the previous 24 h were used as input parameters to predict the SWHs of the future 1, 3, 6, 12, and 24 h. The SWH prediction model was established at three different sites located in the Bohai Sea, the East China Sea, and the South China Sea, separately. The experimental results show that the performance of LSTM and GRU networks based on the gating mechanism was better than that of traditional RNNs, and the performances of the LSTM and GRU networks were comparable. The EMD method was found to be useful in the improvement of the LSTM network to forecast the significant wave heights of 12 and 24 h. |
| 资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19060202] ; National Natural Science Foundation of China[42076214] ; National Natural Science Foundation of China[42006027] ; National Natural Science Foundation of China[U1806227] |
| WOS研究方向 | Engineering ; Oceanography |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000816622700001 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/179689]  |
| 专题 | 海洋研究所_海洋环流与波动重点实验室 |
| 通讯作者 | Hu, Po |
| 作者单位 | 1.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 2.Pilot Natl Lab Marine Sci & Technol Qingdao, Lab Ocean Dynam & Climate, Wenhai Rd 1, Qingdao 266237, Peoples R China 3.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Nanhai Rd, Qingdao 266071, Peoples R China 4.Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266580, Peoples R China |
| 推荐引用方式 GB/T 7714 | Feng, Zhijie,Hu, Po,Li, Shuiqing,et al. Prediction of Significant Wave Height in Offshore China Based on the Machine Learning Method[J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING,2022,10(6):20. |
| APA | Feng, Zhijie,Hu, Po,Li, Shuiqing,&Mo, Dongxue.(2022).Prediction of Significant Wave Height in Offshore China Based on the Machine Learning Method.JOURNAL OF MARINE SCIENCE AND ENGINEERING,10(6),20. |
| MLA | Feng, Zhijie,et al."Prediction of Significant Wave Height in Offshore China Based on the Machine Learning Method".JOURNAL OF MARINE SCIENCE AND ENGINEERING 10.6(2022):20. |
入库方式： OAI收割
来源：海洋研究所
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