AINeutralarXiv – CS AI · 10h ago6/10
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Short-Term Electricity Demand Forecasting for New England Using a Hybrid Transformer-XGBoost Framework with Weather, Calendar, and COVID-19 Indicators
Researchers developed a hybrid machine learning model combining Transformers and XGBoost to forecast short-term electricity demand in New England, incorporating weather, calendar, and COVID-19 data. While the hybrid approach marginally outperformed a baseline model (2.05% MAPE vs 2.21%), statistical testing revealed the improvement is not significant, and an ablation study exposed how COVID-19 features caused overfitting to pandemic-era behavioral patterns that no longer applied.