气候变化领域集成服务门户(CCPortal): A Machine Learning Approach to Developing Ground Motion Models From Simulated Ground Motions

CCPortal

DOI	10.1029/2019GL086690
	A Machine Learning Approach to Developing Ground Motion Models From Simulated Ground Motions
	Withers K.B.; Moschetti M.P.; Thompson E.M.
发表日期	2020
ISSN	0094-8276
卷号	47 期号:6
英文摘要	We use a machine learning approach to build a ground motion model (GMM) from a synthetic database of ground motions extracted from the Southern California CyberShake study. An artificial neural network is used to find the optimal weights that best fit the target data (without overfitting), with input parameters chosen to match that of state-of-the-art GMMs. We validate our synthetic-based GMM with empirically based GMMs derived from the globally based Next Generation Attenuation West2 data set, finding near-zero median residuals and similar amplitude and trends (with period) of total variability. Additionally, we find that the artificial neural network GMM has similar bias and variability to empirical GMMs from records of the recent (Formula presented.) Ridgecrest event, which neither GMM has included in its formulation. As simulations continue to better model broadband ground motions, machine learning provides a way to utilize the vast amount of synthetically generated data and guide future parameterization of GMMs. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.
英文关键词	Learning systems; Neural networks; Seismology; Bias and variability; Earthquake hazard; Ground motion model; Ground motions; Machine learning approaches; Southern California; Synthetic database; Total variabilities; Machine learning; artificial neural network; data set; database; earthquake; ground motion; model validation; parameterization; seismology; simulation; California; United States
语种	英语
来源期刊	Geophysical Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/170578
作者单位	U.S. Geological Survey, Golden, CO, United States
推荐引用方式 GB/T 7714	Withers K.B.,Moschetti M.P.,Thompson E.M.. A Machine Learning Approach to Developing Ground Motion Models From Simulated Ground Motions[J],2020,47(6).
APA	Withers K.B.,Moschetti M.P.,&Thompson E.M..(2020).A Machine Learning Approach to Developing Ground Motion Models From Simulated Ground Motions.Geophysical Research Letters,47(6).
MLA	Withers K.B.,et al."A Machine Learning Approach to Developing Ground Motion Models From Simulated Ground Motions".Geophysical Research Letters 47.6(2020).