| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1563508 | Computational Materials Science | 2009 | 4 Pages |
Abstract
In this paper, a feed-forward multilayer perceptron artificial neural network model is used to simulate the electrical resistivity of nanocrystalline diluted magnetic semiconductors. Variations in the concentrations of Zn, Mn and temperature were used as the model inputs and the resulting electrical resistivity of the nanocrystalline semiconductors as the output of the model. Comparison between the model predictions and the experimental observations predicted a remarkable agreement between them.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
P. Jajarmi, A.R. Eivani,