Paper Info
Title
System reliability analysis of slopes using least squares support vector machines with particle swarm optimization.
Abstract
This paper presents an intelligent response surface method for evaluating system failure probability of soil slopes based on least squares support vector machines (LSSVM) and particle swarm optimization. A novel machine learning technique LSSVM is adopted to establish the response surface to approximate the limit state function based on the samples generated by computer experiments. Subsequently, the proposed response surface is utilized in conjunction with Monte Carlo simulation to obtain the desired reliability estimation. The hyper-parameters which are crucial to the performance of LSSVM are selected by a swarm intelligence algorithm called particle swarm optimization. Experimental results on three examples show that the proposed system reliability analysis method is promising for soil slopes with obvious system effects.
Year
DOI
Venue
2016
10.1016/j.neucom.2015.11.122
Neurocomputing
Keywords
Field
DocType
Slope stability,System probabilistic analysis,LSSVM,Particle swarm optimization,Response surface
Least squares,Particle swarm optimization,Computer experiment,Monte Carlo method,Mathematical optimization,Support vector machine,Swarm intelligence,Multi-swarm optimization,Artificial intelligence,Machine learning,Mathematics,Limit state design
Journal
Volume
Issue
ISSN
209
C
0925-2312
Citations 
PageRank 
References 
5
0.51
13
Authors
3
Name
Order
Citations
PageRank
Fei Kang170.94
Jing-shuang Li250.51
Junjie Li33012.76