Efficient deep learning-based prediction of floor response spectra for nuclear power plants using a multi-head attention-based convolutional bidirectional long short-term memory network

Key Points

• The study predicts floor response spectra using a deep learning model, enhancing accuracy and reliability.
• Key metrics indicate that the model achieved a significant reduction in prediction error, improving safety designs.
• Assessment using a multi-head attention-based convolutional bidirectional long short-term memory network optimizes predictions.
• This approach may enable better design and safety measures, though it requires further validation in real-world scenarios.