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To achieve an accurate and comprehensive prediction of the SST change over time, a 3DCNN-LSTM-AT Model based on time characteristics is proposed which can capture the correlations of SST across both space and time. A series of experiments on the tasks of the short, medium and long-term SST predictions in Bohai Sea and the South China Sea demonstrate that the proposed model has achieved an ideal effect and outperforms the persistence model. Further improvements to the model will be made later to further improve the prediction accuracy and the training and computational efficiency of the model.
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IEEE/ICACT20210141 Slide.19
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