Table 1 Hyperparameters and corresponding values that are tested during the random search

Scaling

{ None, Z-Score, Min-Max Scaling }

Training algorithm

{ SGD, AdaGrad, RMSProp, Adam }

Activation function

{ Sigmoid, ReLU, tanh, linear (in the output layer) }

Hours of input data

{ 24 × 3, 24 × 5, 24 × 7, 24 × 9 }

Learning rate

{lr_d×10⁻¹,lr_d,lr_d×10¹,lr_d×10²} with (lr_d) = default learning rate of the

corresponding optimiser as implemented in the python keras api

Hidden layers

{1,2,3,4}

Decay

{0,0.0001,0.001,0.01}

Patience of early stopping

{10,20,30}

Test split

{0.25,0.3,0.35}

L²−Regularisation

λ∈{ 0, 0.001, 0.01, 0.1}

Dropout

{ 0.1, 0.2, 0.3 }