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DOI | 10.1002/2017GL072716 |
Enabling large-scale viscoelastic calculations via neural network acceleration | |
DeVries, Phoebe M. R.1,2; Ben Thompson, T.1,2; Meade, Brendan J.1,2 | |
2017-03-28 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS
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ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2017 |
卷号 | 44期号:6 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity is the computational costs of large-scale viscoelastic earthquake cycle models. Computationally intensive viscoelastic codes must be evaluated at thousands of times and locations, and as a result, studies tend to adopt a few fixed rheological structures and model geometries and examine the predicted time-dependent deformation over short (<10years) time periods at a given depth after a large earthquake. Training a deep neural network to learn a computationally efficient representation of viscoelastic solutions, at any time, location, and for a large range of rheological structures, allows these calculations to be done quickly and reliably, with high spatial and temporal resolutions. We demonstrate that this machine learning approach accelerates viscoelastic calculations by more than 50,000%. This magnitude of acceleration will enable the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible. |
英文关键词 | viscoelastic earthquake cycle models artificial neural networks |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000399762700006 |
WOS关键词 | HECTOR-MINE-EARTHQUAKE ; NORTH ANATOLIAN FAULT ; INTERNAL DEFORMATION ; DISLOCATION SOURCE ; STRESS TRANSFER |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/27213 |
专题 | 气候变化 |
作者单位 | 1.Harvard Univ, Dept Earth & Planetary Sci, Cambridge, MA USA; 2.Harvard Univ, Dept Earth & Planetary Sci, 20 Oxford St, Cambridge, MA 02138 USA |
推荐引用方式 GB/T 7714 | DeVries, Phoebe M. R.,Ben Thompson, T.,Meade, Brendan J.. Enabling large-scale viscoelastic calculations via neural network acceleration[J]. GEOPHYSICAL RESEARCH LETTERS,2017,44(6). |
APA | DeVries, Phoebe M. R.,Ben Thompson, T.,&Meade, Brendan J..(2017).Enabling large-scale viscoelastic calculations via neural network acceleration.GEOPHYSICAL RESEARCH LETTERS,44(6). |
MLA | DeVries, Phoebe M. R.,et al."Enabling large-scale viscoelastic calculations via neural network acceleration".GEOPHYSICAL RESEARCH LETTERS 44.6(2017). |
条目包含的文件 | 条目无相关文件。 |
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