Long-Term Prediction of Sea Surface Temperature by Temporal Embedding Transformer With Attention Distilling and Partial Stacked Connection

Sea surface temperature (SST) is one of the most important parameters in the global ocean–atmosphere system, and its long-term changes will have a significant impact on global climate and ecosystems. Accurate prediction of SST, therefore, especially the improvement of long-term predictive ski...

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Detalhes bibliográficos

Principais autores:	Hao Dai, Zhigang He, Guomei Wei, Famei Lei, Xining Zhang, Weijie Zhang, Shaoping Shang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2024-01-01
coleção:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Assuntos:	Attention distilling China Sea long-term prediction partial stacked connection sea surface temperature (SST) temporal transformer
Acesso em linha:	https://ieeexplore.ieee.org/document/10414022/
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