Fig. 3: Performance of convolutional neural network (CNN) models in predicting the structural capacity of deteriorated girders.

a The models evaluation is conducted based on artificial corrosion data developed with a methodology presented in the methods section. For the classification models, confusion matrices for b two, c three, and d five classes. Diagonal elements represent the number of points for which the predicted remaining capacity range is equal to the true range. e For the regression model, the blue solid line represents the perfect prediction, while estimations lying above this line underestimate the actual capacities. Black color points illustrate estimations with the proposed CNN Model, points in red and blue are predictions using the average and minimum thickness as corrosion input to an analytical tool, respectively. Nowadays, structural evaluation of corroded girders is conducted with the use of similar equations. Capacities for subfigures (b–d) are normalized with respect to the capacity of 33WF130 girder without section loss.