Predicting largest expected aftershock ground motions using automated machine learning (AutoML)-based scheme
Abstract Aftershocks can cause additional damage or even lead to the collapse of structures already weakened by a mainshock. Scarcity of in-situ recorded aftershock accelerograms heightens the need to develop synthetic aftershock ground motions. These synthesized motions are crucial for assessing th...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-84668-7 |
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