DocumentCode :
3358813
Title :
Study on pavement design based on MC-SVM method of reliability
Author :
Chen, Guoqing ; Su, Guoshao
Author_Institution :
State Key Lab. of Geohazard Prevention & Geoenvironment Protection, Chengdu Univ. of Technol., Chengdu, China
fYear :
2010
fDate :
26-28 June 2010
Firstpage :
4877
Lastpage :
4880
Abstract :
Aiming at reliability analysis problems with implicit performance functions and strongly nonlinear features in the pavement engineering, a new method for reliability analysis based on mente carlo(MC) theory and support vector machine(SVM) is developed. Due to strongly nonlinear mapping ability of SVM, the SVM model is employed to establish the nonlinear mapping relationship between basic random variables and engineering structural response action. SVM model is learned by samples generated from uniform design method and FLAC3D programs. The learned SVM model is integrated with Monte Carlo method to calculate the failure probability and reliability. The validity of the proposed method is verified by one pavement engineering examples, it has better precision and high efficiency. The results are in good agreement with the actual situations, and the experience and method could benefit other similar projects.
Keywords :
Monte Carlo methods; civil engineering computing; design engineering; failure (mechanical); probability; reliability; roads; support vector machines; FLAC3D programs; Monte Carlo method; engineering structural response action; failure probability; nonlinear mapping relationship; pavement design; pavement engineering; reliability analysis problem; support vector machine; Design engineering; Design methodology; Laboratories; Performance analysis; Probability; Protection; Random variables; Reliability engineering; Reliability theory; Support vector machines; monte carlo; pavement engineering; reliability; support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
Type :
conf
DOI :
10.1109/MACE.2010.5536201
Filename :
5536201
Link To Document :
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