Prediction of a stress-strain curve of ferrite-martensite DP steels was studied by a combined technique of Bayesian inference and artificial neural network. To screen a descriptor to be used for neural network analysis, material genomes such as volume fraction, micro-hardness, handle, and void of martensite phase, and micro-hardness of ferrite phase were examined by Bayesian inference. In a case of small data set, a machine learning method to predict mechanical properties reliably was proposed.
CITATION STYLE
Adachi, Y., Shinkawata, K., Okuno, A., Hirokawa, S., Taguchi, S., & Sadamatsu, S. (2016). High dimensional microstructure data-driven prediction of stress-strain curve of DP steels by primary artificial intelligence. Tetsu-To-Hagane/Journal of the Iron and Steel Institute of Japan, 102(1), 47–55. https://doi.org/10.2355/tetsutohagane.TETSU-2015-069
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