Foundation pit displacement monitoring and prediction using least squares support vector machines based on multi-point measurement

Xiao Li, Xin Liu, Clyde Zhengdao Li, Zhumin Hu, Geoffrey Qiping Shen, Zhenyu Huang

Research output: Journal article publication › Journal article › Academic research › peer-review

Original language	Others/Unknown
Pages (from-to)	715-724
Number of pages	10
Journal	Structural Health Monitoring
Volume	18
Issue number	3
Publication status	Published - 2019

Cite this

@article{3ef47418e11149bd910dde4a1c1783c1,

title = "Foundation pit displacement monitoring and prediction using least squares support vector machines based on multi-point measurement",

author = "Xiao Li and Xin Liu and Li, {Clyde Zhengdao} and Zhumin Hu and Shen, {Geoffrey Qiping} and Zhenyu Huang",

year = "2019",

language = "Others/Unknown",

volume = "18",

pages = "715--724",

journal = "Structural Health Monitoring",

issn = "1475-9217",

publisher = "SAGE Publications Ltd",

number = "3",

}

TY - JOUR

T1 - Foundation pit displacement monitoring and prediction using least squares support vector machines based on multi-point measurement

AU - Li, Xiao

AU - Liu, Xin

AU - Li, Clyde Zhengdao

AU - Hu, Zhumin

AU - Shen, Geoffrey Qiping

AU - Huang, Zhenyu

PY - 2019

Y1 - 2019

M3 - Journal article

SN - 1475-9217

VL - 18

SP - 715

EP - 724

JO - Structural Health Monitoring

JF - Structural Health Monitoring

IS - 3

ER -