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Demand Forecasting in Smart Grid Using Long Short-Term Memory [article]

Koushik Roy, Abtahi Ishmam, Kazi Abu Taher
2021 arXiv   pre-print
In this paper, an LSTM based model using neural network architecture is proposed to forecast power demand.  ...  Long Short-Term Memory (LSTM) shows promising results in predicting time series data which can also be applied to power load demand in smart grids.  ...  Finally, the LSTM is a modified recurrent neural network (RNN) with a chain like structure that is suitable for predictions where long-term dependency is an issue [14] .  ... 
arXiv:2107.13653v1 fatcat:4dv3gasqb5e2bhbh4u6rl4ym3y