Exploring the possibility of assessing the damage degree of liquefaction based only on seismic records by artificial neural networks

Exploring the possibility of assessing the damage degree of liquefaction based only on seismic records by artificial neural networks

This study presents a new approach to determine the damage degree of liquefaction caused by a large earthquake. We propose an artificial neural network (ANN) model based only on the seismic records of ground and define the degree of liquefaction “DDL” as a damage index. This ANN model predicts the d...

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Bibliographic Details
Main Authors: Akiyoshi Kamura, Go Kurihara, Tomohiro Mori, Motoki Kazama, Youngcheul Kwon, Jongkwan Kim, Jin-Tae Han
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Soils and Foundations
Subjects:
Liquefaction
Machine learning
Artificial neural network
Shaking table test
Seismic records
Classification Problems
Online Access:http://www.sciencedirect.com/science/article/pii/S0038080621000470

Internet

http://www.sciencedirect.com/science/article/pii/S0038080621000470

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