Machine Learning-Based Seismic Reliability Assessment of Bridge Networks

Transportation networks are critical components of lifeline systems. They can experience disruptions due to seismic hazards that could lead to severe emergency response and recovery problems. Finding an efficient and effective method to evaluate the seismic reliability of bridge networks is crucial for risk managers. This study proposes a method that can compute the seismic reliability of bridge networks using machine learning techniques. The proposed method is computationally less expensive than existing methods and can be implemented easily in emergency risk management systems. Moreover, it includes information on ranking bridges and prioritizing retrofit plans.

Automated summary

Transportation networks are crucial for emergency response and recovery, but they can be disrupted by seismic hazards. This study proposes a computationally efficient method using machine learning techniques to evaluate the seismic reliability of bridge networks, providing information for ranking bridges and prioritizing retrofit plans.