Optimization of Earthquake-Resistant Structural Design Using Artificial Intelligence Algorithms

The increasing frequency and intensity of seismic events have highlighted the critical need for resilient structural design in civil engineering. Traditional methods for designing earthquake-resistant structures often face limitations in addressing complex, nonlinear behaviors and multi-objective optimization requirements, which can compromise structural performance and safety. The present study investigates the application of artificial intelligence (AI) algorithms to optimize earthquake-resistant structural design, aiming to enhance both the efficiency and resilience of building systems under seismic loads. A qualitative, descriptive, and library-based research approach was employed, involving an extensive review of scientific literature from peer-reviewed journals and authoritative databases. The study focuses on AI-driven optimization techniques, including evolutionary algorithms, particle swarm optimization, artificial neural networks, and hybrid methods, alongside advanced modeling and simulation strategies to predict structural responses, define design parameters, and evaluate performance under earthquake conditions. The findings indicate that AI algorithms significantly improve the design process by enabling multi-objective optimization, accurately modeling nonlinear structural behavior, and providing data-driven predictive capabilities. Furthermore, AI-based methods facilitate the identification of optimal material usage, cost-effective design solutions, and enhanced seismic resilience compared to conventional approaches. The integration of AI into structural engineering practices not only reduces the reliance on extensive physical testing but also supports the development of innovative and adaptive design strategies that can respond to dynamic and uncertain seismic environments. These results suggest that AI has become an indispensable tool for achieving safer, more efficient, and sustainable earthquake-resistant structures, offering substantial benefits to engineers and stakeholders involved in seismic risk mitigation.

کلیدواژه ها:

earthquake-resistant design ، structural optimization ، artificial intelligence ، seismic resilience