MC-FSTG: A fine-grained spatio-temporal graph neural network based on multi-scale operating conditions for bearing temperature prediction in high-speed trains
Key Points
Improved temperature prediction accuracy with the MC-FSTG model is significant for high-speed trains.
The model achieved a 15% increase in prediction accuracy compared to traditional methods.
Observational analysis across varying operating conditions demonstrated the model's robustness and adaptability.
This finding may enable better maintenance strategies, reducing potential failures in complex transportation systems.
MC-FSTG: Uma rede neural gráfica espatio-temporal de alta resolução baseada em condições operacionais multiescala para previsão da temperatura de rolamentos em trens de alta velocidade | Synapse