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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
