New Publication in AIP Advances
Undergraduate researcher Jun Young Lee published a paper on long-term permanent magnet synchronous motor temperature prediction in AIP Advances.
Undergraduate researcher Jun Young Lee and colleagues published the paper “Adaptive Sequence-to-Sequence Learning for Long-Term Permanent Magnet Synchronous Motor Temperature Prediction” in AIP Advances.
The study proposes sequence-to-sequence learning methods for accurate and stable long-term prediction of permanent magnet temperature.
The proposed models incorporate adaptive normalization, probabilistic teacher forcing, and an attention mechanism to improve long-horizon prediction performance.