4.6 Article

Determination of liquefaction susceptibility of soil: a least square support vector machine approach

Publisher

WILEY
DOI: 10.1002/nag.2081

Keywords

liquefaction; least square support vector machine; artificial neural network; SPT; prediction

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This article adopts least square support vector machine (LSSVM) for determination of liquefactions susceptibility of soil based on standard penetration test data. Two models (Models I and II) have been developed. For Model I, input variables are cyclic stress ratio and standard penetration test value (N). Model II employs peak ground acceleration and N as input variables. The developed LSSVM models (Models I and II) give equations for determination of liquefaction susceptibility of soil. The performances of Models I and II are the same. The developed LSSVM gives probabilistic output. The results of LSSVM have been compared with the artificial neural network model. This article shows that N and the peak ground acceleration are sufficient input parameters for determination of liquefaction susceptibility of soil. Copyright (c) 2012 John Wiley & Sons, Ltd.

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