Cargando…
Decision Tree Approach for Soil Liquefaction Assessment
In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893014/ https://www.ncbi.nlm.nih.gov/pubmed/24489498 http://dx.doi.org/10.1155/2013/346285 |
_version_ | 1782299620171317248 |
---|---|
author | Gandomi, Amir H. Fridline, Mark M. Roke, David A. |
author_facet | Gandomi, Amir H. Fridline, Mark M. Roke, David A. |
author_sort | Gandomi, Amir H. |
collection | PubMed |
description | In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view. |
format | Online Article Text |
id | pubmed-3893014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-38930142014-02-02 Decision Tree Approach for Soil Liquefaction Assessment Gandomi, Amir H. Fridline, Mark M. Roke, David A. ScientificWorldJournal Research Article In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view. Hindawi Publishing Corporation 2013-12-30 /pmc/articles/PMC3893014/ /pubmed/24489498 http://dx.doi.org/10.1155/2013/346285 Text en Copyright © 2013 Amir H. Gandomi et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gandomi, Amir H. Fridline, Mark M. Roke, David A. Decision Tree Approach for Soil Liquefaction Assessment |
title | Decision Tree Approach for Soil Liquefaction Assessment |
title_full | Decision Tree Approach for Soil Liquefaction Assessment |
title_fullStr | Decision Tree Approach for Soil Liquefaction Assessment |
title_full_unstemmed | Decision Tree Approach for Soil Liquefaction Assessment |
title_short | Decision Tree Approach for Soil Liquefaction Assessment |
title_sort | decision tree approach for soil liquefaction assessment |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893014/ https://www.ncbi.nlm.nih.gov/pubmed/24489498 http://dx.doi.org/10.1155/2013/346285 |
work_keys_str_mv | AT gandomiamirh decisiontreeapproachforsoilliquefactionassessment AT fridlinemarkm decisiontreeapproachforsoilliquefactionassessment AT rokedavida decisiontreeapproachforsoilliquefactionassessment |