@inproceedings{38d058e968694c38abc7db21576b4601,
title = "Arch bridge suspender tension identification by using neural network",
abstract = "The measurement of arch bridge suspender tension using vibration method is mostly considered that the suspender is idealized as taut strings. This idealization simplifies the analysis but may introduce unacceptable errors in many applications by ignoring the boundary condition and bending stiffness effects. The neural network intelligent methodology is proposed to compute suspenders tension, and design steps and optimization methods of neural network are given. In order to get correct neural network predictive model, 200 data of 20 bridges is used to train the neural network. The applicability of the proposed intelligent methodology is verified by comparison with the others method through a case. The result shows that the error isn't beyond percent of 6.",
keywords = "Arch bridge suspender, Neural network, Suspender tension identification, Vibration method",
author = "Dongsheng Li and Jinping Ou",
year = "2010",
doi = "10.1117/12.846724",
language = "英语",
isbn = "9780819480651",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
number = "PART 1",
booktitle = "Health Monitoring of Structural and Biological Systems 2010",
edition = "PART 1",
note = "Health Monitoring of Structural and Biological Systems 2010 ; Conference date: 08-03-2010 Through 11-03-2010",
}