| 基于时间序列分析的滑坡变形动态预测研究 |
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| 引用本文： | 邓继辉,陈柏林. 基于时间序列分析的滑坡变形动态预测研究[J]. 长江科学院院报, 2012, 29(10): 78-81. DOI: 10.3969/j.issn.1001-5485.2012.10.015 |
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| 作者姓名： | 邓继辉 陈柏林 |
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| 作者单位： | 1.中国煤炭科工集团重庆设计研究院,重庆,400016;2.重庆地质矿产研究院,重庆,400042 |
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| 摘 要： | 针对以往变形预测模型实用性不足的缺点,基于时间序列分析原理,结合系统论和岩土体流变理论,在深入研究影响滑坡变形的外界主控环境变量的基础上,采用移动平均法和多项式函数对位移时序的趋势项进行抽取和建模,用支持向量机建立起环境主控变量与位移偏离项之间的非线性关系,并根据变形对外界环境响应情况建立起动态预测模型.将此预测思路和方法应用于三峡库区某滑坡,通过实例研究表明:该预测思路和方法合理可行,不但具有较强的建模能力、且有较高的精度,可用于相关的工程实践之中.
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| 关 键 词： | 滑坡 变形预测 时间序列分析 移动平均法 支持向量机 |
| 收稿时间： | 2011-05-10 |
| 修稿时间： | 2011-07-06 |
Dynamic Prediction of Landslide Deformation Based on Time Series Analysis |
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| DENG Ji-hui , CHEN Bo-lin. Dynamic Prediction of Landslide Deformation Based on Time Series Analysis[J]. Journal of Yangtze River Scientific Research Institute, 2012, 29(10): 78-81. DOI: 10.3969/j.issn.1001-5485.2012.10.015 |
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| Authors: | DENG Ji-hui CHEN Bo-lin |
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| Affiliation: | 1.Chongqing Design and Research Institute, China Coal Technology & Engineering Group, Chongqing400016, China; 2.Chongqing Institute of Geology and Mineral Resources, Chongqing 400042, China |
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| Abstract: | On account of the lack of practicality in landslide deformation prediction models,a dynamic prediction model was established on the basis of time series analysis,system theory and rock-soil rheology theory.The maximum water level,maximum fluctuation,and maximum drawdown speed between two adjacent monitoring processes were chosen as the main external control variables.The trend item of displacement time sequence was extracted and modeled by moving average method and polynomial function,and the nonlinear relation between deviate item and environmental control variables was modeled by support vector machine.The dynamic model can be constructed according to the response of the deformation to the environmental variables.The method is applied to the deformation prediction of landslide in Three Gorges reservoir area.Result shows that this method not only has strong modeling capability but also has high accuracy and can be used in project programs. |
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| Keywords: | landslide deformation prediction time series analysis moving average method support vector machine |
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