Machine learning-based estimation method of seismic response of building’s unobserved floor

Abstract. There is a need for technology that can automatically and immediately identify and evaluate the structural integrity of a building. This study aims to propose a method that utilizes machine learning to estimate the building responses of unobserved floors based on strong motion records. Numerical experiments were performed using a seismic response analysis model of RC super high-rise buildings to assess the estimation accuracy. As a result, the estimation accuracy was improved by increasing the amount of data used for training.