Site amplification prediction model of shallow bedrock sites based on machine learning models

Article Geochemistry & Geophysics

Machine-Learning-Based Surface Ground-Motion Prediction Models for South Korea with Low-to-Moderate Seismicity

Hwanwoo Seo et al.

Summary: This study proposes ground-motion prediction models based on machine learning techniques and compares their performance. The gradient boosting model shows the best performance and the study analyzes its working process and important variables. The results of this research are significant for improving ground-motion prediction.

BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA (2022)

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Article Engineering, Civil

How well can we predict earthquake site response so far? Site-specific approaches

Chuanbin Zhu et al.

Summary: This article tests and compares different estimation techniques in predicting the outcrop Fourier site responses, finding that the empirical correction method can better capture the characteristics of site responses.

EARTHQUAKE SPECTRA (2022)

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Article Engineering, Civil

Simulation-based site amplification model for shallow bedrock sites in Korea

Muhammad Aaqib et al.

Summary: A new simulation-based site amplification model for shallow sites in Korea has been developed, consisting of linear and nonlinear components. The model shows similarities to amplification equations developed for the western United States at short periods, but exhibits distinct characteristics between 0.1 and 0.5 seconds corresponding to the natural periods of shallow sites.

EARTHQUAKE SPECTRA (2021)

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Article Geochemistry & Geophysics

Estimation of Site Ampllification from Geotechnical Array Data Using Neural Networks

Daniel Roten et al.

Summary: The study uses deep learning to predict surface-to-borehole Fourier amplification functions, training two neural networks and achieving up to 50% reduction in prediction errors. In the future, data-driven prediction of site response may become independent of proxies or simplifying assumptions.

BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA (2021)

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Article Engineering, Geological