Guest editorial for the special issue on artificial intelligence, sensing and big data analytics in earthquake engineering
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10518-024-01920-1.pdf
Reference12 articles.
1. Abdelmalek-Lee E, Burton H (2023) A dual Kriging-XGBoost model for reconstructing building seismic responses using strong motion data. Bull Earthq Eng. https://doi.org/10.1007/s10518-023-01624-y
2. Achmet Z, Diamantopoulos S, Fragiadakis M (2023) Rapid seismic response prediction of rocking blocks using machine learning. Bull Earthq Eng. https://doi.org/10.1007/s10518-023-01680-4
3. Ancheta TD et al (2014) NGA-West2 database. Earthq Spectra 30(3):989–1005. https://doi.org/10.1193/070913EQS197M
4. Bindi D, Massa M, Luzi L, Ameri G, Pacor F, Puglia R, Augliera P (2014) Pan-european ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods up to 3.0s using the RESORCE dataset. Bull Earthq Eng 12:391–430. https://doi.org/10.1007/s10518-013-9525-5
5. Giardina G, Macchiarulo V, Foroughnia F et al (2023) Combining remote sensing techniques and field surveys for post-earthquake reconnaissance missions. Bull Earthq Eng. https://doi.org/10.1007/s10518-023-01716-9
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