BRIDGE DAMAGE IDENTIFICATION BASED ON GENETIC OPTIMIZATION NEURAL NETWORKS ALGORITHM
As many bridges have been installed with monitoring systems presently, automatic damage detection becomes a core technique of bridge health monitoring systems, which attracts the attention of many researchers. Based on the characteristics of artificial neural networks and genetic algorithm, a new approach, genetic optimization and neural networks hybrid algorithm, is put forward to identify the damage location and degree of bridge structure. Compared with the traditional artificial neural networks algorithm, the global convergence effect of this hybrid algorithm is enhanced by use of the optimization rule of the genetic algorithm in the searching process. A testing data are analyzed with this method and the results are compared with those due to other methods. The results show that this method is rational and credible.
Miao-Yi Deng Jin-Chao Yue Ju-Yin Cu
College of Civil Engineering and Architecture, Fuzhou University, P.R. China School of Environment a School of Environment and Water Conservancy, Zhengzhou University, P.R. China College of Civil Engineering and Architecture, Fuzhou University, P.R. China
国际会议
长沙
英文
623-626
2007-11-19（万方平台首次上网日期，不代表论文的发表时间）