Machine learning techniques for estimating seismic site amplification in the Santiago basin, Chile-Reference-Cited by-同舟云学术

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Machine learning techniques for estimating seismic site amplification in the Santiago basin, Chile

Published:2022-09 Issue: Volume:306 Page:106764
ISSN:0013-7952
Container-title:Engineering Geology
language:en
Short-container-title:Engineering Geology

Author:

Díaz J.P.,Sáez E.,Monsalve M.,Candia G.,Aron F.,González G.

Funder

Agencia Nacional de Investigacion y Desarrollo

Publisher

Elsevier BV

Subject

Geology,Geotechnical Engineering and Engineering Geology

Reference72 articles.

1. Space and time spectra of stationary stochastic waves, with special reference to microtremors;Aki;Bull. Earthq. Res. Inst.,1957

2. Local site effect on ground motion;Aki,1988

3. Evaluating machine learning approaches for the interpolation of monthly air temperature at Mt. Kilimanjaro, Tanzania;Appelhans;Spatial Stat.,2015

4. Seismic microzoning of Arica and Iquique, Chile;Becerra;Nat. Hazards,2015

5. Predicting soil properties in the Canadian boreal forest with limited data: Comparison of spatial and non-spatial statistical approaches;Beguin;Geoderma,2017

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2. Performance of Different ANNs in Microtremor H/V Peak Classification;Seismological Research Letters;2024-06-18

3. Bibliometric analysis of artificial intelligence techniques for predicting soil liquefaction: insights and MCDM evaluation;Natural Hazards;2024-05-09

4. A comparative analysis of ensemble learning algorithms with hyperparameter optimization for soil liquefaction prediction;Environmental Earth Sciences;2024-05

5. Spatial correlation models of VS30 values: A case study of the Tehran region;Engineering Geology;2023-11

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