Vision-aided vibration analysis and comfort evaluation of a pedestrian bridge via Bayesian-optimised BiLSTM neural network

Key Points

• Vibration analysis and comfort evaluation identify key aspects for pedestrian bridge safety and user experience.
• Critical metrics on performance and comfort are established through advanced methods involving bayesian optimization and neural networks.
• Assessment using a Bayesian-optimised BiLSTM neural network demonstrates the potential for enhanced predictive accuracy in bridge monitoring.
• Implications of these findings suggest a shift towards more responsive and intelligent infrastructure management, addressing user comfort.