Machine Learning Applications in Geotechnical Earthquake Engineering: Progress, Gaps, and Opportunities-Reference-Cited by-同舟云学术

Machine Learning Applications in Geotechnical Earthquake Engineering: Progress, Gaps, and Opportunities

Published:2023-03-23 Issue: Volume: Page:
ISSN:
Container-title:Geo-Congress 2023
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Author:

Cheng Katherine¹²,Ziotopoulou Katerina¹²

Affiliation:

1. Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA.

2. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784484692.050

Reference60 articles.

1. Evaluation of lateral spreading using artificial neural networks

2. A neural network for automated quality screening of ground motion records from small magnitude earthquakes;Bellagamba X.;Earthquake Spectra,2019

3. Regularized estimation of large covariance matrices;Bickel P. J.;The Annals of Statistics,2008

4. Estimation of liquefaction-induced horizontal displacements using artificial neural networks;Chiru-Danzer M.;Canadian Geot J,2001

5. A comparison of artificial neural network and classical regression models for earthquake-induced slope displacements;Cho Y.;Soil Dyn & Earthq Eng,2022

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