首页> 外文会议>International Conference on Structural Condition Assessment, Monitoring and Improvement;SCAMI-2 >BRIDGE DAMAGE IDENTIFICATION BASED ON GENETIC OPTIMIZATION NEURAL NETWORKS ALGORITHM
【24h】

BRIDGE DAMAGE IDENTIFICATION BASED ON GENETIC OPTIMIZATION NEURAL NETWORKS ALGORITHM

机译:基于遗传优化神经网络算法的桥梁损伤识别

获取原文

摘要

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.
机译:当前,由于许多桥梁都安装了监视系统,因此,自动损伤检测已成为桥梁健康监视系统的一项核心技术,引起了众多研究者的关注。根据人工神经网络和遗传算法的特点,提出了一种新的方法,即遗传优化和神经网络混合算法,以识别桥梁结构的损伤位置和程度。与传统的人工神经网络算法相比,在搜索过程中利用遗传算法的优化规则,增强了该混合算法的全局收敛性。用这种方法分析测试数据,并将结果与​​其他方法的结果进行比较。结果表明,该方法是合理,可靠的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号