A Review of the Advances of Artificial Intelligence and Its Application in Earthquake Engineering

Earthquake engineering faces complex challenges in predicting seismic events, assessing structural integrity, and mitigating risks, necessitating innovative solutions to enhance safety and resilience. Artificial Intelligence (AI) has emerged as a transformative tool, leveraging its ability to process vast datasets and model nonlinear relationships to address these challenges. This review explores AI's applications across key areas: earthquake detection and early warning systems, ground motion prediction, structural health monitoring, seismic hazard and risk assessment, post-earthquake damage evaluation, and seismic design and retrofitting optimization. Main findings highlight AI's superior performance in real-time signal classification, data-driven ground motion models, automated damage detection, and optimized retrofit strategies, driven by techniques like Convolutional Neural Networks, Long Short-Term Memory networks, and ensemble methods. Trends indicate a shift toward hybrid models integrating physics-based simulations and edge AI for scalable, real-time solutions. Despite challenges like data scarcity and model interpretability, AI's trajectory promises to revolutionize earthquake engineering, fostering more resilient infrastructure and communities through continued innovation and collaboration.

کلیدواژه ها:

Artificial Intelligence ، Machine Learning ، Deep Learning ، Earthquake Engineering