Peak ground acceleration estimation using P-wave parameters and horizontal-to-vertical spectral ratios

Ting Yu Hsu, Rih Teng Wu, Chia Wei Liang, Chun Hsiang Kuo, Che Min Lin

研究成果: 雜誌貢獻期刊論文同行評審

3 引文 斯高帕斯(Scopus)

摘要

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.

原文???core.languages.en_GB???
頁(從 - 到)1-8
頁數8
期刊Terrestrial, Atmospheric and Oceanic Sciences
31
發行號1
DOIs
出版狀態已出版 - 1 2月 2020

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