基于条件生成对抗网络的高频磁性元件铁损预测

This article tackles the complex challenge of predicting magnetic iron losses in high-frequency magnetic components by introducing a novel conditional generative adversarial network model. Diverging from traditional loss prediction methodologies that often overlook intricate interactions of factors, our conditional generative adversarial network framework is designed to comprehensively incorporate...