Peak ground acceleration estimation using P-wave parameters and horizontal-to-vertical spectral ratios
Journal
Terrestrial, Atmospheric and Oceanic Sciences
Journal Volume
31
Journal Issue
1
Pages
1-8
Date Issued
2020
Author(s)
Abstract
Peak ground acceleration (PGA) can be used to estimate the seismic intensity. However, using P-wave features to estimate PGA is a challenging task. One of the reasons for that is that a seismic wave commonly undergoes modification due to various site effects, consequently leading to uncertainty in the predicted PGA. In order to accommodate site effects using site parameters together with P-wave parameters, this paper takes advantage of machine learning to consider multiple parameters simultaneously. Several artificial neural network (ANN) models considering different site effect parameters are constructed. The performances of these ANN models were investigated and compared. In total, 53531 ground motion data obtained from the Taiwan Strong Motion Instrumentation Program were utilized to develop the proposed approach. It was found that the proposed ANN model with horizontal-to-vertical spectral ratio parameters effectively reduces the error of the estimated PGA when compared with either the ANN model without site parameters or the ANN model with other site parameters. ? 2020 Chinese Geoscience Union. All rights reserved.
Subjects
artificial neural network
ground motion
P-wave
peak acceleration
site effect
Taiwan
Type
journal article