| 基于经验模式分解与LM一BP神经网络的大坝变形预报模型 |
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| 引用本文： | 范千,许承权,方绪华. 基于经验模式分解与LM一BP神经网络的大坝变形预报模型[J]. 福州大学学报(自然科学版), 2011, 39(3): 438-442 |
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| 作者姓名： | 范千 许承权 方绪华 |
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| 作者单位： | 福州大学土木工程学院;闽江学院地理科学系; |
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| 基金项目： | 福建省教育厅科研资助项目(JA10045); 江西省数字国土重点实验室开放基金资助项目(DLLJ201102); 福建省自然科学基金资助项目(2009J05102); 福州大学科研启动基金资助项目(022355) |
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| 摘 要： | 提出一种基于经验模式分解(EMD)与LM-BP神经网络相结合的模型进行大坝变形预报的方法.先利用EMD具有根据信号本身特征进行自适应分解的功能将变形时间序列分解为一系列不同尺度的固有模式分量IMF,再根据各个IMF的变化规律采用相匹配的LM-BP模型进行预报,最后对各分量的预报值进行叠加得到最终的变形预报结果.实例分析...
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| 关 键 词： | 经验模式分解 神经网络 大坝 变形 预报 |
Dam deformation prediction model based on empirical mode decomposition and LM-BP neural network |
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| FAN Qian,XU Cheng-quan,FANG Xu-hua. Dam deformation prediction model based on empirical mode decomposition and LM-BP neural network[J]. Journal of Fuzhou University(Natural Science Edition), 2011, 39(3): 438-442 |
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| Authors: | FAN Qian XU Cheng-quan FANG Xu-hua |
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| Affiliation: | FAN Qian1,XU Cheng-quan2,FANG Xu-hua1(1.College of Civil Engineering,Fuzhou University,Fuzhou,Fujian 350108,China,2.Department of Geography,Minjiang University,China) |
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| Abstract: | A novel model based on empirical mode decomposition(EMD) and neural network for dam deformation prediction is presented in the paper.Firstly,considering that EMD has an advantage to do adaptive decomposition according to characteristics of the signal itself,deformation time series is decomposed into a series of intrinsic mode functions(IMF) in different scale space.Then,according to the change regulation of each IMF,they are forecasted by appropriate LM-BP neural networks.Finally,these forecasting results o... |
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| Keywords: | empirical mode decomposition neural network dam deformation prediction |
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