Existing forecasting methods often force a trade-off: either train a highly specialized model for each site (which is costly and doesn't scale) or adapt a large, general-purpose model (which can be ...
Abstract: Existing time-series forecasting methods often struggle to adapt to dynamic scenarios and lack flexibility in prediction. They typically require retraining the model when the prediction ...
Abstract: The expansion of data centers, driven by 5G and artificial intelligence adoption, significantly increases energy consumption. Note utilizing clean energy is crucial for data centers to ...
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