Least Square Support Vector Machine Applied to Slope Reliability Analysis

被引：33
|
作者：
Samui P. [1 ]
Lansivaara T. [2 ]
Bhatt M.R. [3 ]
机构：
[1] Centre for Disaster Mitigation and Management, VIT University, Vellore
[2] Department of Civil Engineering, Tampere University of Technology, Tampere
[3] School of Mechanical and Building Science, VIT University, Vellore
来源：
Geotech. Geol. Eng. | 2013年 / 4卷 / 1329-1334期
关键词：
First order second moment (FOSM) method; Implicit performance function; Least square support vector machine; Slope reliability;
D O I：
10.1007/s10706-013-9654-2
中图分类号：
学科分类号：
摘要：
This paper investigates the feasibility of Least square support vector machine (LSSVM) model to cope the problem of implicit performance function during first order second moment (FOSM) method based slope reliability analysis. LSSVM is firmly based on the theory of statistical learning. In LSSVM, Vapnik's ε -insensitive loss function has been replaced by a cost function which corresponds to a form of ridge regression. Here, LSSVM has been used as a regression technique to approximate implicit performance functions. A slope example has been presented for illustrating the applicability of LSSVM based FOSM method. The developed LSSVM based FOSM has been compared with the artificial neural network (ANN) and least square method. The result shows that the approximation of LSSVM can be used in the FOSM method for slope reliability analysis. © 2013 Springer Science+Business Media Dordrecht.
引用
收藏
页码：1329 / 1334
页数：5
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