| Autor: |
Niketa Sharma, Harish Sharma, Ashish Sharma, Yogendra Gupta |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Communication and Intelligent Systems ISBN: 9789811610882 |
| DOI: |
10.1007/978-981-16-1089-9_2 |
| Popis: |
In this paper, we have proposed electrothermal modeling of GaN-based HEMT devices. A data-driven approach has been implemented for a temperature range varying from 300 to 600 K, based on one of the core methods of machine learning techniques based on decision tree (DT). The performance of the proposed models was validated through the simulated test examples. The attained outcomes depicted that the developed models predict the HEMT device characteristics accurately depending on the determined mean-squared error (MSE) between the actual and anticipated characteristics. The paper also indicates that the decision tree technique could be specifically beneficial when data are nonlinear and multidimensional, with the different process parameters exhibited profoundly complex interactions. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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