| 大坝变形的神经网络方法研究 |
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| 引用本文： | 仲洁,牛哲.大坝变形的神经网络方法研究[J].江苏测绘,2012(5):14-16. |
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| 作者姓名： | 仲洁 牛哲 |
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| 作者单位： | [1]东南大学交通学院测绘工程系,江苏南京211189 [2]东南大学交通学院道路桥梁与渡河工程系,江苏南京211189 |
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| 摘 要： | 大坝的失事带来的不仅是经济损失也是安全隐患，因此，建立一种大坝变形长期预测模型对它的安全评价将具有重要意义。本文针对华东CC大坝5JHJl04监测点的垂直位移变形进行分析，在传统的回归分析模型和常规神经网络模型的基础上建立了将两种方法结合的融合模型，得到大坝变形分析的最优模型。其精度与一般方法相比有了进一步的提升，可以更好地进行大坝变形预测。
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| 关 键 词： | BP神经网络 回归分析 大坝变形 预测 |
Dam Deformation of Neural Networks |
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| ZHONG Jie,NIU Zhe.Dam Deformation of Neural Networks[J].Jiangsu Surveying and Mapping,2012(5):14-16. |
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| Authors: | ZHONG Jie NIU Zhe |
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| Institution: | 1 Survey Department of Transportation College, Southeast University, Nanjing Jiangsu 211189, China 2 RoadsBridges Department of Transportation College, Southeast University, Nanjing Jiangsu 211189, China) |
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| Abstract: | The dam accident brings not only economic losses but also security risks. Therefore, to establish a long term forecasting model of dam safety evaluation of the dam is of great significance. Our project researches in the vertical deformation of Anhui CC 5 JHJ 104 monitoring point, making use of the neural network model, the traditional regression model and the integration of the two methods combined model. Accuracy of the models are compared and analyzed, therefore, we can finally get a best model. |
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| Keywords: | BP neural network statistical model fusion model dam deformation prediction |
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