| 用人工神经网络方法评估桥梁缺损状况 |
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| 引用本文： | 韩大建,杨炳尧,颜全胜. 用人工神经网络方法评估桥梁缺损状况[J]. 华南理工大学学报(自然科学版), 2004, 32(9): 72-75,96 |
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| 作者姓名： | 韩大建 杨炳尧 颜全胜 |
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| 作者单位： | 华南理工大学,建筑学院,广东,广州,510640;华南理工大学,建筑学院,广东,广州,510640;华南理工大学,建筑学院,广东,广州,510640 |
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| 基金项目： | 广州市科技攻关引导项目 (2 0 0 2Z3 D30 31) |
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| 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1018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；位确率超过60％．平均每座桥的评估误差为0．25个等级。
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| 关 键 词： | 人工神经网络 桥梁评估 学习向量量化网络 径向基网络 Elman网络 |
| 文章编号： | 1000-565X(2004)09-0072-04 |
An Artificial Neural Network Method to Evaluate Bridge Damage Conditions |
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| Han Da-jian Yang Bing-yao Yan Quan-sheng. An Artificial Neural Network Method to Evaluate Bridge Damage Conditions[J]. Journal of South China University of Technology(Natural Science Edition), 2004, 32(9): 72-75,96 |
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| Authors: | Han Da-jian Yang Bing-yao Yan Quan-sheng |
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| 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. |
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| Keywords: | artificial neural network bridge evaluation LVQ network RBF network Elman network |
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