Seismic liquefaction potential assessment by using Relevance Vector Machine

被引:0
作者
Pijush Samui
机构
[1] Indian Institute of Science,Department of Civil Engineering
来源
Earthquake Engineering and Engineering Vibration | 2007年 / 6卷
关键词
liquefaction; cone penetration test; relevance vector machine; artificial neural network;
D O I
暂无
中图分类号
学科分类号
摘要
Determining the liquefaction potential of soil is important in earthquake engineering. This study proposes the use of the Relevance Vector Machine (RVM) to determine the liquefaction potential of soil by using actual cone penetration test (CPT) data. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The results are compared with a widely used artificial neural network (ANN) model. Overall, the RVM shows good performance and is proven to be more accurate than the ANN model. It also provides probabilistic output. The model provides a viable tool for earthquake engineers to assess seismic conditions for sites that are susceptible to liquefaction.
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收藏
页码:331 / 336
页数:5
相关论文
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