In a groundbreaking development, researchers have introduced a cutting-edge method for real-time structural response prediction, poised to redefine the landscape of disaster prevention and building resilience. The innovative approach combines physics-informed deep learning with a data-driven training strategy, revolutionizing the accuracy and efficiency of structural response prediction. Detailed structural diagram of the Phy-Seisformer model. This novel method, known as the Phy-Seisformer model, incorporates the physical information of a structure into its predictive capabilities, enabling higher-precision forecasts. Through extensive experimentation on various building structures, including masonry and reinforced concrete, the method has demonstrated unparalleled accuracy and exceptional computational speed, outperforming traditional finite element calculations by at least 5000 times. The implications of this research are far-reaching, offering a potential paradigm shift in post-eart...
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