6 citations · 8 across the 4 of their papers we have counts for
4 papers
Transfer Learning-Based Surrogate Modeling for Nonlinear Time-History Response Analysis of High-Fidelity Structural Models
Keiichi Ishikawa, Yuma Matsumoto, Taro Yaoyama +2
In a performance based earthquake engineering (PBEE) framework, nonlinear time-history response analysis (NLTHA) for numerous ground motions are required to assess the seismic risk…
Waveform-Based Probabilistic Seismic Hazard Analysis Using Ground-Motion Generative Models
Yuma Matsumoto, Taro Yaoyama, Sangwon Lee +2
In probabilistic seismic hazard analysis (PSHA), the exceedance probability of a ground-motion intensity measure (IM) is typically evaluated. However, in recent years, dynamic resp…
Site-Specific Ground Motion Generative Model for Crustal Earthquakes in Japan Based on Generative Adversarial Networks
Yuma Matsumoto, Taro Yaoyama, Sangwon Lee +2
We develop a site-specific ground-motion model (GMM) for crustal earthquakes in Japan that can directly model the probability distribution of ground motion acceleration time histor…
Latent Space-Based Likelihood Estimation Using a Single Observation for Bayesian Updating of a Nonlinear Hysteretic Model
Sangwon Lee, Taro Yaoyama, Yuma Matsumoto +2
This study presents a novel approach to quantifying uncertainties in Bayesian model updating, which is effective in sparse or single observations. Conventional uncertainty quantifi…