Artificial intelligence approach on predicting current values of polymer interface Schottky diode based on temperature and voltage: An experimental study
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Academic Press Ltd- Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, an artificial neural network model has been developed to predict the current values of a 6H?SiC/MEH-PPV Schottky diode with polymer-interface, depending on temperature and voltage. In the training of the multi-layer perceptron network model with 13 neurons in its hidden layer, the experimentally measured current values between 100 and 250 K temperature and -3V to + 3V voltage range have been used. In the input layer of the model developed with a total of 244 experimental data, temperature, and voltage values have been defined and current values were obtained in the output layer. The mean square error value of the artificial neural network is 1.63E-08 and the R-value is 0.99999. The developed model has been able to predict the current values of the polymer-interfaced 6H?SiC/MEH-PPV Schottky diode with an average error rate of -0.15% depending on temperature and voltage, with high accuracy.
Açıklama
Anahtar Kelimeler
Schottky diode, Barrier diode, MEH-PPV, Current-voltage characteristics, Artificial neural network
Kaynak
Superlattices and Microstructures
WoS Q Değeri
Q2
Scopus Q Değeri
Q2
Cilt
153
