| 基于径向基网络的钢管混凝土拱桥承载力评价 |
| |
| 引用本文： | 刘沐宇,冯清海.基于径向基网络的钢管混凝土拱桥承载力评价[J].武汉理工大学学报,2005,27(11):46-49. |
| |
| 作者姓名： | 刘沐宇 冯清海 |
| |
| 作者单位： | 武汉理工大学道路桥梁与结构工程湖北省重点实验室,武汉,430070 |
| |
| 基金项目： | 湖北省自然科学基金(2003ABA016)，湖北省交通厅科技攻关项目(2003年) |
| |
| 摘 要： | 在现有桥梁承载力评价方法的基础之上,针对BP神经网络评价方法的缺陷,引入径向基网络理论,提出了钢管混凝土拱桥承载力径向基网络评价方法.以承载力评价为总体目标,从影响承载力的几个方面进行考虑,建立了RBF神经网络评价模型,通过样本学习训练,获取专家经验知识的直觉思维.通过工程实例验证,评价结果较好地反映了桥梁结构的安全性状况,证明了该评价方法的可行性与实用性.
|
| 关 键 词： | 钢管混凝土拱桥 安全性评价 径向基神经网络 |
| 文章编号： | 1671-4431(2005)11-0046-04 |
| 修稿时间： | 2005年5月30日 |
Safety Assessment of CFST Arch Bridge Based on Radial Basis Function Neural Network |
| |
| LIU Mu-yu,FENG Qing-hai.Safety Assessment of CFST Arch Bridge Based on Radial Basis Function Neural Network[J].Journal of Wuhan University of Technology,2005,27(11):46-49. |
| |
| Authors: | LIU Mu-yu FENG Qing-hai |
| |
| Abstract: | An approach to load bearing evaluation for concrete-filled steel tube(CFST) arch bridge based on the RBF neural network was presented.Several factors were taken into consideration,and RBFNN was built to get the result of load bearing assessment of CFST arch bridge.RBFNN was trained through inputting samples.The approach had some advantages over BP,such as not falling into district minimize,highly effective training.It was illustrated for the long-span concrete-filled steel tube arch bridge in Wuhan,China.The result showed that the approach was highly potential and practical in assessing the safety of long-span concrete-filled steel tube arch bridge. |
| |
| Keywords: | CFST arch bridge safety assessment radial basis function neural network(RBFNN) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
