Title :
Study on support vector machine in evalluation of bridge structural health monitoring
Author :
Wang, Jingyan ; Tan, Li ; Yu, Chongchong
Author_Institution :
Dept of Comput. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
Abstract :
Structural distortion of bridge contains rich connotation information of bridge structures and possesses the features of nonlinear, sequential and small sample capacity. In this article, the evaluation model of bridge structural distortion is established by application of support vector machine and the practical monitoring data of Hangzhou Bay Bridge are taken as the study object. The feasibility and effectiveness of evaluation over bridge structural health state have been proved through test, and the superiority of least square support vector machine in distortion prediction has been shown on comparison of test results.
Keywords :
bridges (structures); condition monitoring; least squares approximations; structural engineering; support vector machines; Hangzhou bay bridge; bridge structural health monitoring; connotation information; distortion prediction; least square support vector machine; sample capacity; structural distortion; Kernel; Monitoring; Support vector machines; Tin; bridge structural health monitoring; distortion; least squares support vector machine;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658334