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| 基于主成分和半参数的大坝变形监测回归模型 | |
| 引用本文： | 许昌,岳东杰,董育烦,邓成发.基于主成分和半参数的大坝变形监测回归模型[J].岩土力学,2011,32(12):3738-3742. |
| 作者姓名： | 许昌 岳东杰 董育烦 邓成发 |
| 作者单位： | 1. 浙江水利水电专科学校市政工程系,杭州310018;河海大学地球科学与工程学院,南京210098 2. 河海大学地球科学与工程学院,南京,210098 3. 中国水电顾问集团华东勘测设计研究院,杭州,310014 4. 浙江省水利河口研究院,杭州,310020 |
| 基金项目： | 浙江省水利厅科技计划项目 |
| 摘 要： | 主成分分析在一定程度上可以解决大坝变形监测回归模型因子间的复共线性,然而当提取的主成分信息不充分时,主成分回归用于大坝安全预测可能失效。提出以主成分分析提取的主成分作为半参数回归的参数分量,剩余成分和模型误差作为未知的非参数分量对主成分回归进行补偿,建立一种基于主成分和半参数的大坝变形监测混合回归模型。利用某大坝实测资料进行建模分析,结果表明该混合模型能克服回归因子间的复共线性,避免半参数回归补偿最小二乘估计中法矩阵的病态性,比传统的主成分回归和逐步回归模型具有更好的拟合和预报精度。 |
| 关 键 词： | 大坝 复共线性 主成分分析 半参数回归 补偿最小二乘 |
| 收稿时间： | 2010-06-08 |
Regression model for dam deformation based on principal component and semi-parametric analysis |
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| XU Chang,YUE Dong-jie,DONG Yu-fan,DENG Cheng-fa.Regression model for dam deformation based on principal component and semi-parametric analysis[J].Rock and Soil Mechanics,2011,32(12):3738-3742. | |
| Authors: | XU Chang YUE Dong-jie DONG Yu-fan DENG Cheng-fa |
| Institution: | 1. Department of Municipal Engineering, Zhejiang Water Conservancy and Hydropower College, Hangzhou 310018, China; 2. School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China; 3. East China Investigation and Design Institute, China Hydropower Engineering Consulting Group Corporation, Hangzhou 310014, China; 4. Zhejiang Institute of Hydraulics & Estuary, Hangzhou 310020, China |
| Abstract: | Principal component analysis(PCA) is a solution to the multicollinearity problem of dam regression models.However,uninformative principal components(PCs) may lead to the failure prediction of dam deformation.Thus a hybrid regression model using semi-parametric regression and PCA is proposed,where the PCs with the highest variance are treated as the semi-parametric component;the remaining PCs and model errors are treated as the non-parametric component to be estimated.The hybrid model is tested using the fie... |
| Keywords: | dam multicollinearity principal component analysis semi-parametric regression compensated least squares |
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