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Mobarak Abumohsen

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Electrical Load Forecasting Using LSTM, GRU, and RNN Algorithms

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By Mobarak Abumohsen, Amani Yousef Owda, Majdi Owda, Amani Yousef
| MDPI
4.1.4. Forecasting Using LSTM, RNN, and GRU Algorithms with Adadelta Optimizer In this section, the results obtained from LSTM, RNN, and GRU algorithms will be discussed using one and multiple hidden layers in addition to the input and output layer on each model with the dropout in Adadelta optimizer. Figure 19 shows the actual and predicted results in forecasting the STLF using the LSTM, GRU, and RNN models. Where the test result values were taken from each learning rate.
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