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Experiments As shown in Figure 3, the predicted red curve closely aligns with the actual blue curve across most time steps, demonstrating high consistency in overall trends, minimal errors between predicted, actual values · 2021 · arXiv 2020.29914

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Accurate Prediction of Temperature Indicators in Eastern China Using a Multi-Scale CNN-LSTM-Attention model

cs.LG · 2024-12-11 · reject · novelty 2.0

A CNN-LSTM-Attention model predicts eastern China temperature with reported MSE 1.98, but the RMSE value contradicts the MSE and no baselines are shown.

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Accurate Prediction of Temperature Indicators in Eastern China Using a Multi-Scale CNN-LSTM-Attention model cs.LG · 2024-12-11 · reject · none · ref 4
A CNN-LSTM-Attention model predicts eastern China temperature with reported MSE 1.98, but the RMSE value contradicts the MSE and no baselines are shown.

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