海洋预报2025，Vol.42Issue(1)：11-22,12.DOI:10.11737/j.issn.1003-0239.2025.01.002
基于LSTM的北极海冰范围多步预测策略研究
Research on multi-step prediction strategies of Arctic sea ice extent based on Long Short-Term Memory
摘要
Abstract
While previous researches have primarily focused on single-step prediction of Arctic sea ice extent,multi-step prediction and strategy are yet to be explored.This study utilizes monthly average Arctic sea ice extent data spanning from 1978 to 2022 and employs Long Short-Term Memory to implement multi-step predictions of Arctic sea ice extent for the next 12 months using four strategies:Recursive,Direct,Multi-input Multi-output,and Seq2Seq.The results show that a model input length of 24 months performs optimally.When compared to the other three basic multi-step prediction strategies,the Seq2Seq strategy demonstrates superior accuracy in forecasting Arctic sea ice extent over the next 12 months,with an root mean square error of 0.33 million square kilometers.关键词
北极海冰范围/长短期记忆网络/多步预测策略/Seq2Seq策略Key words
Arctic sea ice extent/Long Short-Term Memory/multi-step prediction strategies/Seq2Seq分类
海洋学引用本文复制引用
王漫漫,邹斌,石立坚,曾韬,张颖,路敦旺..基于LSTM的北极海冰范围多步预测策略研究[J].海洋预报,2025,42(1):11-22,12.基金项目
国家重点研发计划项目(2021YFC2803300、2022YFC2807003). （2021YFC2803300、2022YFC2807003）
