A 1D-CNN deep learning framework for seismic collapse prediction of jacket offshore platforms with Bayesian neural architecture search

Key Points

• Seismic collapse prediction accuracy improved by utilizing a 1D-CNN deep learning framework.
• The Bayesian neural architecture search achieved a significant accuracy increase in predictions by adapting model parameters dynamically.
• Assessment using deep learning techniques evaluates the structural integrity of jacket offshore platforms under seismic loads.
• Findings suggest that advances in predictive modeling may enhance safety regulations for offshore structures.