#7247. Modeling of Schottky diode characteristic by machine learning techniques based on experimental data with wide temperature range

October 2026publication date
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Journal’s subject area:
Condensed Matter Physics;
Electrical and Electronic Engineering;
Materials Science (all);
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Abstract:
In this study, common machine learning methods have been used to model the characteristic of the Schottky diode. The current values of previously produced Schottky diode against the voltages applied to the diode terminal were measured. After determining the combinations and specifications for each one that provide the lowest model error of each model, the performances of the obtained models were compared with each other concerning the various performance indices. The performance of the ANFIS model was found to be much better than the others Therefore, it was proposed as a powerful tool for modeling at all temperature values between 40K and 400K.
Keywords:
Machine learning; Schottky diode; Temperature based I–V characteristic

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