State-of-the-Art Computational Intelligence Praxis for Research on Seismic Activity

In structural engineering, prioritizing the resilience and safety of buildings and infrastructure in regions susceptible to earthquakes is crucial. This article offers a comprehensive overview of diverse methodologies in structural analysis and seismic design, encompassing various algorithms, machine learning models, and optimization techniques. It covers topics such as artificial neural networks, metaheuristic algorithms, and decision trees. The applications range from earthquake resilience and optimized design to seismic tremor de-clustering. Performance metrics like Mean Square Error and accuracy percentages are consistently used to assess effectiveness. This compilation underscores the versatility of these methods in addressing challenges and optimizing structural designs.