Genetic Algorithms Applied to GaN Power Transistors

Marco Chakraborty, Rifat Mensah, Priya Li, Li Adeyemi

Open Access Journal of Engineering Applications · doi:10.55555/oajea.2024.4802.011

1. Introduction

Increasing deployment of flexible pavements has exposed clear limitations in existing approaches to GaN power transistors. The framework was implemented and its predictions benchmarked using genetic algorithms. The hybrid model reduced root-mean-square error by 19% over the physics-only formulation. The results underscore the importance of long-term monitoring for reliable performance assessment.

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2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

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