9、Building Energy Load Forecasting using Deep Neural Networks
亮點：考慮了LSTM和S2S的不同層結構對訓練和測試集的結構影響。 基於深度神經網絡的建築能量負荷預測網絡 所介紹的工作調查了兩個LSTM基礎架構：1）標準LSTM和2）基於LSTM序列到序列（S2S）架構。 兩種方法都是在電力消耗的基準數據集上實施來自一個住宅客戶的數據。 這兩種架構都是經過一小時一分鐘的訓練和測試分辨率數據集。 表明標準LSTM在一分鐘分辨率數據時失敗在一小時的分辨率數據中
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相關文章
- 1. 3 Deep Neural Networks for Energy Load Forecasting
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- 4. Neural NILM: Deep Neural Networks Applied to Energy Disaggregation
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