Machine Learning-Based Prediction of Optimal Switch Configurations for Boost Converters by PowerSynth

Authors

Mobolaji Ogunbiyi, University of Arkansas, FayettevilleFollow

Files

Description

Machine Learning-Based Prediction of Optimal Switch Configurations for Boost Converters by PowerSynth

Presented at UA Power Group Undergraduate and REU Summer Research Poster Session on July 18, 2024.

Publication Date

2024

City

Fayetteville

Keywords

REU; Electrical engineering; POETS; NSF

Disciplines

Electrical and Computer Engineering

Comments

Faculty: Dr. Alan Mantooth; Dr. Peng

Mentor: David Setor Agogo Mawuli (UA), Zahra Saadatizadeh (UA)

Citation

Ogunbiyi, M. (2024). Machine Learning-Based Prediction of Optimal Switch Configurations for Boost Converters by PowerSynth. Electrical Engineering Research Experience for Undergraduates. Retrieved from https://scholarworks.uark.edu/elegreu/16