期刊
COMPUTATIONAL MATERIALS SCIENCE
卷 46, 期 1, 页码 124-127出版社
ELSEVIER
DOI: 10.1016/j.commatsci.2009.02.013
关键词
Artificial neural networks; Modeling; Electrical resistivity; Nanocrystalline semiconductors
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. (C) 2009 Elsevier B.V. All rights reserved.
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