Shui-Ze Wang

A federated learning–driven data fusion strategy for the hardenability prediction of gear steel

A federated learning–driven data fusion strategy incorporating a multi-regularized attention residual network model for hardenability prediction (MRAN-J9) is proposed, providing a practical and reliable solution for hardenability prediction in complex industrial application scenarios.