【摘要】 针对现有桥梁评估方法存在的不足 ,介绍了一种应用神经网络进行桥梁缺损状况评估的方法 ,并对几种常见的人工神经网络模型的评估效果进行了比较 .利用广东省内10 18座桥梁的养护数据 ,对神经网络进行训练和测试 ,发现使用神经网络对桥梁进行评估 ,能够取得比较好的评估效果 .使用神经网络方法对桥梁“等级”进行评估 ,其准确率超过 6 0 % ,平均每座桥的评估误差为 0 .2 5个等级 .更多还原

【Abstract】 In view of the weakness of existing bridge evaluat ion methods, a neural network method was first introduced to evaluate the damage conditions of a bridge. The evaluation effects of several common artificial neural network (ANN) models were then compared. The ANN models were finally trained and tested based on the maintenance data of 1018 bridges on the national-grade roads in Guangdong. It is found that the neural network method is effective in evaluating the bridge conditions, more than 60% of the bridge grade being correctly evaluated and the average evaluation error of each bridge being 0.25 grades.更多还原