$13\mathrm{.}2\mathrm{.}12$ An article in Scientia Iranica $[$Tuning the Parameters of an Artificial Neural Network $($ANN$)$ Using Central Com$-$ posite Design and Genetic Algorithm$(2011,$ Vol. $18(6),$ pp$.16001608)]$ described a series of experiments to tune parame$-$ ters in artificial neural networks. One experiment considered the relationship between model fitness $[$measured by the square root of mean square error $($RMSE$)$ on a separate test set of data$]$ and model complexity that were controlled by the number of nodes in the two hidden layers. The following data table $($extracted from a much larger data set$)$ contains three different ANNs: ANN$1$ has $33$ nodes in layer $1$ and $30$ nodes in layer $2,$ ANN$2$ has $49$ nodes in layer $1$ and $45$ nodes in layer $2,$ and ANN$3$ has $17$ nodes in layer $1$ and $15$ nodes in layer $2.$