A Comparison of Neural Networks and Wavelets Networks for Predicting Creep and Rupture Resistance of Ferritic Steels

This work is based in a model of neural and wavelets networks using published experimental data. The objective is to compare a neural and a wavelet network estimating the creep rupture strength based on chemical composition of Fe-2.25Cr-Mo and Fe-(9-12)Cr steels, and on its heat treatment temperature and life time. It will be determined the configuration that provides the best fit of the data.