海洋预报2024，Vol.41Issue(3)：33-43,11.DOI:10.11737/j.issn.1003-0239.2024.03.004
基于LSTM网络的海水温度剖面预报研究
Research on ocean temperature profile forecasts based on Long Short-Term Memory neural network
摘要
Abstract
Based on ocean temperature historical observations and ocean model data,the short-term forecasting method for ocean temperature profile is studied using Long Short-Term Memory(LSTM)neural network.For the ocean temperature profile forecasts at(17°46.91'N,112°03.24'E)in the South China Sea,three sample sets of observation,forecasts,mixed observation-forecasts are constructed using the observational and forecasting data.Based on the LSTM neural network,a many-to-many ocean temperature profile forecasting model composed of encoder and decoder is established,and model training and verification are carried out.The results show that the model has a high forecasting accuracy and a good stability for processing small sample problems.Utilizing deep layered forecasting method can effectively improve the forecasting accuracy and generalization ability.The forecasting error of mixed sample set decreases significantly in comparison with that of observation sample set,which provides an idea for marine environment forecasts of small sample problems.关键词
深度学习/长短期记忆神经网络/海水温度/短时预报Key words
deep learning/LSTM/ocean temperature/short-term prediction分类
海洋科学引用本文复制引用
范培勤,过武宏,唐帅,张驰,曲泓玥..基于LSTM网络的海水温度剖面预报研究[J].海洋预报,2024,41(3):33-43,11.基金项目
基础计划加强重点基础研究项目(2020-JCJQ-ZD-144-00、2020-JCJQ-ZD-144-03). （2020-JCJQ-ZD-144-00、2020-JCJQ-ZD-144-03）
