FTimeXer improves power-grid carbon intensity forecasts by combining an FFT frequency branch with gated fusion and stochastic exogenous masking plus consistency regularization, showing gains on three real datasets.
Dacf: day-ahead carbon intensity forecasting of power grids using machine learning
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FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Footprint Forecasting
FTimeXer improves power-grid carbon intensity forecasts by combining an FFT frequency branch with gated fusion and stochastic exogenous masking plus consistency regularization, showing gains on three real datasets.