An ensemble learning-enhanced collaborative surrogate modeling approach with improved particle swarm optimization for structural reliability assessment

Puntos clave

• Structural reliability assessment improves significantly through ensemble learning techniques, enhancing predictive capabilities.
• The ensemble learning model achieves up to a 25% increase in prediction accuracy compared to traditional models.
• Collaborative surrogate modeling techniques optimize particle swarm optimization, improving parameter tuning in structural assessments.
• Results indicate potential for wide applications in engineering, necessitating further validation in real-world scenarios.