A Comparison of Neural Networks and Wavelets Networks for Predicting Creep and Rupture Resistance of Ferritic Steels 2007-01-2827
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.
Citation: Penha, R. and Franceschini Canale, L., "A Comparison of Neural Networks and Wavelets Networks for Predicting Creep and Rupture Resistance of Ferritic Steels," SAE Technical Paper 2007-01-2827, 2007, https://doi.org/10.4271/2007-01-2827. Download Citation
Author(s):
Renata Neves Penha, Lauralice C. Franceschini Canale
Affiliated:
Universidade de São Paulo, São Carlos, SP, Brazil
Pages: 8
Event:
SAE Brasil 2007 Congress and Exhibit
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Neural networks
Heat treatment
Drag
Chemicals
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