| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1562896 | Computational Materials Science | 2009 | 5 Pages |
Abstract
The oxidation behavior of hot pressed nanocrystalline Cr-33Nb alloys was modeled using a feed-forward multilayer Perceptron artificial neural network model. It was found that the artificial neural networks model is an applicable method for prediction of the oxidation behavior of hot pressed nanocrystalline Cr-33Nb alloys. The optimum number of the neurons and hidden layers to do this simulation was 16 and 16, respectively.
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Authors
P. Jajarmi, S. Valipour,