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Table 2 (abstract P5). Best neural network parameterization for prosumers and non-prosumers

From: Abstracts from the 9th DACH+ Conference on Energy Informatics

  Non-Prosumer Prosumer
Optimizer Adam Adam
Learning rate 0.001 0.001
Loss function MAE MSE
Number of hidden layers 3 5
Number of neurons per hidden layer 1000 500
Activation function ReLu ReLu
Early stopping algorithm patience 20 20
Validation split 0.1 0.1
Combination of lagged input variables 7 4