Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression

Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or...

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Main Authors: Zhang, Wengang, Goh, Anthony Teck Chee
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/89975
http://hdl.handle.net/10220/46449
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-899752020-03-07T11:43:39Z Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression Zhang, Wengang Goh, Anthony Teck Chee School of Civil and Environmental Engineering Multivariate Adaptive Regression Splines Logistic Regression DRNTU::Engineering::Civil engineering Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising. Published version 2018-10-26T06:36:51Z 2019-12-06T17:37:50Z 2018-10-26T06:36:51Z 2019-12-06T17:37:50Z 2016 Journal Article Zhang, W., & Goh, A. T. (2016). Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression. Geomechanics and Engineering, 10(3), 269-284. doi:10.12989/gae.2016.10.3.269 2092-6219 https://hdl.handle.net/10356/89975 http://hdl.handle.net/10220/46449 10.12989/gae.2016.10.3.269 en Geomechanics and Engineering © 2016 Techno-Press, Ltd. This paper was published in Geomechanics and Engineering and is made available as an electronic reprint (preprint) with permission of Techno-Press, Ltd. The published version is available at: [http://dx.doi.org/10.12989/gae.2016.10.3.269]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 16 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Multivariate Adaptive Regression Splines
Logistic Regression
DRNTU::Engineering::Civil engineering
spellingShingle Multivariate Adaptive Regression Splines
Logistic Regression
DRNTU::Engineering::Civil engineering
Zhang, Wengang
Goh, Anthony Teck Chee
Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression
description Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Zhang, Wengang
Goh, Anthony Teck Chee
format Article
author Zhang, Wengang
Goh, Anthony Teck Chee
author_sort Zhang, Wengang
title Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression
title_short Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression
title_full Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression
title_fullStr Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression
title_full_unstemmed Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression
title_sort evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression
publishDate 2018
url https://hdl.handle.net/10356/89975
http://hdl.handle.net/10220/46449
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