Estimation of thermally stimulated current in as grown TlGaSeS layered single crystals by multilayered perceptron neural network
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Date
2011-06
Journal Title
Journal ISSN
Volume Title
Publisher
Pergamon-Elsevier Science
Abstract
This paper presents an artificial neural network approach to compute thermally stimulated current (TSC) in as-grown T1GaSeS layered single crystals. The experimental data have been obtained from TSC measurements. The network has been trained by a genetic algorithm (GA). The results confirmed that the proposed model could provide an accurate computation of the TSC.
Description
Keywords
Computer science, Engineering, Operations research & management science, Semiconductors, Thermally stimulated current, Neural network, Genetic algorithm, Optical-properties, Trap distribution, Absorption, Photoconductivity, Tlins2, Genetic algorithms, Single crystals, Thermoluminescence, Artificial neural network approach, As-grown, Experimental data, Multi-layered, Perceptron neural networks, Semiconductors, Thermally stimulated current, Neural networks
Citation
Küçük, İ. vd. (2011). "Estimation of thermally stimulated current in as grown TlGaSeS layered single crystals by multilayered perceptron neural network". Expert Systems with Applications, 38(6), 7192-7194.