改进RBF网络及其在悬索桥吊索损伤定位中的应用

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英文篇名：Modified RBF Neural Network and Its Application at Sling Damage Location of Suspension Bridges 中文刊名：南京航空航天大学学报 英文刊名：Journal of Nanjing University of Aeronautics & Astronautics 作者：杨杰 ; 李爱群 ; 曾捷 英文作者：Yang Jie1 ; 2 ; Li Aiqun2 ; Zeng Jie1(1.College of Aerospace Engineering ; Nanjing University of Aeronautics & Astronautics ; Nanjing ; 210016 ; China ; 2.College of Civil Engineering ; Southeast University ; Nanjing ; 210096 ; China) 中文关键词：损伤定位 ; 径向基函数 ; 改进算法 英文关键词：damage location ; radial basis function ; modified algorithm 出版日期：2011-02-15 机构：南京航空航天大学航空宇航学院;东南大学土木工程学院; 年：2011 期：01 出版单位：南京航空航天大学学报

摘要

研究了RBF网络行为的过拟合现象,提出了基于R2+准则与Jackknife校验的改进算法。以润扬大桥南汊悬索桥为背景,在对其吊索损伤分析的基础上,构建了RBF损伤定位网络。研究表明,本文提出的改进RBF网络可以较好地对吊索进行损伤定位。
By studying an OLS-RBF learning algorithm,a modified algorithm based on R2+ rule and Jackknife validation is presented.After analyzing the sling damage patterns of the Runyang Yangtze river highway bridge-south suspension bridge,the RBF damage location network is constructed,trained and tested. Results show that modified RBF network can effectively locate the sling damage.

引文

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