Digital Design
Conditional Generative Adversarial Network Aided Iron Loss Prediction for High-Frequency Magnetic Components
Audience:
Artificial Intelligence Professionals, Automotive Component Manufacturers, Automotive Component Suppliers, Automotive Designers, Automotive Engineers, Circular Economy Experts, Digital Design Professionals, Electric Vehicle Manufacturers
Artificial Intelligence Professionals, Automotive Component Manufacturers, Automotive Component Suppliers, Automotive Designers, Automotive Engineers, Circular Economy Experts, Digital Design Professionals, Electric Vehicle Manufacturers
Keyword:
Conditional Generative Adversarial Network, Deep Neural Network, E-Volve Cluster, High-Frequency Magnetic Components, Multilayer Perceptron, POWERDRIVE, Volumetric Iron Losses
Conditional Generative Adversarial Network, Deep Neural Network, E-Volve Cluster, High-Frequency Magnetic Components, Multilayer Perceptron, POWERDRIVE, Volumetric Iron Losses
Link:
IEEE Xplore