Multi-step forecasting of ocean wave height using gate recurrent unit networks with multivariate time series

Li Xinfang; Cao Jinfeng; Guo JihongLiu ChaoWang WenJia ZhenSu Tianyun

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Multi-step forecasting of ocean wave height using gate recurrent unit networks with multivariate time series

机译：Multi-step forecasting of ocean wave height using gate recurrent unit networks with multivariate time series

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摘要

Ocean wave height is an essential parameter for ocean engineering construction, planning decisions, and coastal hazards assessment. Long-term, accurate, and reliable ocean wave height forecasts are critical for the purposes mentioned above and have attracted more attention in recent years. This work proposed a novel method that achieves robust short-term and long-term ocean wave forecasting via the gate recurrent unit (GRU) network. The GRU-based wave forecasting model is established to learn long-term dependency among multivariate sequential data. The future wave height is predicted based on learned features via the proposed method. Case studies of 6 different stations along the coast of China are investigated. The results show that for 1-hour forecasts, the GRU network is superior to comparison methods in terms of all the error metrics. For 3-hour forecasts, the GRU network shows more robustness compared to the LSTM algorithm. The results also validate that the presented scheme is an efficient and reliable short-term and long-term wave forecasting approach. Applying the forecasting method in reality is essential for ocean safety, ocean exploitation, and many other fields.

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来源
《Ocean engineering》 |2022年第15期|110689.1-110689.13|共13页
作者
Li Xinfang; Cao Jinfeng; Guo JihongLiu ChaoWang WenJia ZhenSu Tianyun;
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作者单位

Minist Nat Resources, Inst Oceanog 1, Qingdao 266061, Peoples R China;

Qingdao Univ Technol, Shandong Technol Res Ctr Accid Prevent Key Ind Fi, Sch Mech & Automot Engn, Qingdao 266520, Peoples R China;

China Univ Min & Technol, Sch Energy & Min Engn, Beijing 100083, Peoples R ChinaTsinghua Univ, Dept Energy & Power Engn, State Key Lab Control & Simulat Power Syst & Gene, Beijing 100084, Peoples R ChinaMinist Nat Resources, Inst Oceanog 1, Qingdao 266061, Peoples R China|Natl Engn Lab Integrated AeroSp Ground Ocean Big, Xian, Peoples R ChinaMinist Nat Resources, Inst Oceanog 1, Qingdao 266061, Peoples R China|Natl Engn Lab Integrated AeroSp Ground Ocean Big, Xian, Peoples R China|Pilot Natl Lab Marine Sci & Technol, Lab Reg Oceanog & Numer Modeling, Qingdao, Peoples R China;

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正文语种英语
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Ocean wave height forecasting; Gated recurrent unit network; Long short-term memory network; Machine learning; Multivariate time series;

Multi-step forecasting of ocean wave height using gate recurrent unit networks with multivariate time series

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