| 利用经验模态分解和LSSVM预测隧道不均匀沉降 |
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| 引用本文： | 汤俊,邹自力,张晓平.利用经验模态分解和LSSVM预测隧道不均匀沉降[J].测绘科学,2011,36(3):29-31. |
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| 作者姓名： | 汤俊 邹自力 张晓平 |
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| 作者单位： | 1. 东华理工大学资环系,南昌,330013
2. 东华理工大学,地球科学与测绘工程学院,江西抚州,344000 |
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| 基金项目： | 东华理工大学校长基金(DHXK1010); 江西省数字国土重点实验室开放基金(DLLJ201014) |
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| 摘 要： | 隧道不均匀沉降是个复杂的系统.针对其非线性、非平稳的特点,本文将经验模态分解(EMD)和最小二乘支持向量机(LSSVM)引入该领域,建立了一种基于EMD和LSSVM的预测模型.首先,利用EMD方法将原始序列作平稳化处理,得到一系列本征模态分量(IMF);其次,根据各个IMF的变化规律,采用合适的参数构造不同的LSSVM...
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| 关 键 词： | 经验模态分解 最小二乘支持向量机 隧道 不均匀沉降预测 |
Uneven settlement prediction of tunnel based on EMD and LSSVM |
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| TANG Jun,ZOU Zi-li,ZHANG Xiao-ping.Uneven settlement prediction of tunnel based on EMD and LSSVM[J].Science of Surveying and Mapping,2011,36(3):29-31. |
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| Authors: | TANG Jun ZOU Zi-li ZHANG Xiao-ping |
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| Institution: | ②(①Department of Resources and Environmental Engineering,East China Institute of Technology,Nanchang 330013,China;②College of Earth Sciences and Mapping Engineering,East China Institute of Technology,Jiangxi Fuzhou 344000,China) |
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| Abstract: | Uneven settlement of the tunnel is a complex system.Due to the non-linear and non-stationary characteristics,the paper led the empirical mode decomposition(EMD) and least squares support vector machine(LSSVM) into the field to establish a kind of model prediction based on EMD and LSSVM.First,it used the EMD method to smooth processing for the original sequence to get a series of intrinsic mode components(IMF);second,according to the change rule of each IMF,it used he appropriate parameters of LSSVM to const... |
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| Keywords: | empirical mode decomposition least squares support vector machine tunnel uneven settlement prediction |
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