Machine learning-based estimation method of seismic response of building’s unobserved floor
Year: 2025
Type: conference-paper
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.
Source: Materials research proceedings
Author: Daiki Kakehashi
Institution: Ibaraki University
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408405876