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Table 2 Computational results of RMSE during the training and validation processes with different neurons of hidden layer in ANN models. RMSE is the root means square error calculated by Eq. (3)

From: Prediction of phenolic compounds and glucose content from dilute inorganic acid pretreatment of lignocellulosic biomass using artificial neural network modeling

Neurons in hidden layer, n RMSE for CGlc after 500 iterations RMSE for CPhe after 500 iterations
Training dataset Validation dataset Training dataset Validation dataset
n = 3 7.16 7.12 0.54 0.41
n = 4 9.35 8.51 0.87 0.42
n = 5 7.92 6.06 0.56 0.18
n = 6 6.71 6.41 1.37 1.05
n = 7 6.44 5.47 0.46 0.22
n = 8 7.53 5.84 0.46 0.46
n = 9 6.41 5.03 0.42 0.40
n = 10 6.40 5.20 0.43 0.28
n = 11 6.57 4.97 0.53 0.25
n = 12 6.38 4.73 0.43 0.24
n = 13 6.50 5.46 0.43 0.32