Faster Post-Earthquake Damage Assessment Based on 1D Convolutional Neural Networks
Contemporary deep learning approaches for post-earthquake damage assessments based on 2D convolutional neural networks (CNNs) require encoding of ground motion records to transform their inherent 1D time series to 2D images, thus requiring high computing time and resources. This study develops a 1D...
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Autores principales: | Xinzhe Yuan, Dustin Tanksley, Liujun Li, Haibin Zhang, Genda Chen, Donald Wunsch |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/e2ae3fa7137a4d019489ac7204158710 |
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