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ENTITY District heating systems load forecasting: a deep neural networks model based on similar day approach

District heating systems load forecasting: a deep neural networks model based on similar day approach

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  1. RESEARCH · CL_198192 ·

    XGBoost outperforms LSTM in heat energy forecasting study

    A new research paper compares XGBoost and Long-Short Term Memory (LSTM) for forecasting heat energy in district heating systems. The study found that XGBoost consistently outperformed LSTM, particularly in areas with le…