基于变系数回归模型的三峡库区滑坡位移预测

喻孟良; 梅红波; 李冀骅; 赵慧; 吴润泽

doi:10.3799/dqkx.2016.118

Volume 41 Issue 9

Sep. 2016

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Article Navigation > Earth Science > 2016 > 41(9): 1593-1602

Yu Mengliang, Mei Hongbo, Li Jihua, Zhao Hui, Wu Runze, 2016. Landslide Displacement Prediction Based on Varying Coefficient Regression Model in Three Gorges Reservoir Area. Earth Science, 41(9): 1593-1602. doi: 10.3799/dqkx.2016.118

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Yu Mengliang, Mei Hongbo, Li Jihua, Zhao Hui, Wu Runze, 2016. Landslide Displacement Prediction Based on Varying Coefficient Regression Model in Three Gorges Reservoir Area. Earth Science, 41(9): 1593-1602. doi: 10.3799/dqkx.2016.118

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Landslide Displacement Prediction Based on Varying Coefficient Regression Model in Three Gorges Reservoir Area

doi: 10.3799/dqkx.2016.118

Yu Mengliang^{1,2
,},
Mei Hongbo^{3
,
,},
Li Jihua⁴,
Zhao Hui²,
Wu Runze⁵

1.
Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
2.
China Institute of Geo-Environment Monitoring, Beijing 100081, China
3.
Faculty of Earth Resources, China University of Geosciences, Wuhan 430074, China
4.
School of Computer Science, China University of Geosciences, Wuhan 430074, China
5.
Command of Geological Hazard Control in Three Gorges Reservoir Area, Yichang 443000, China

Received Date: 2016-01-22
Publish Date: 2016-09-15

Abstract

Abstract

Landslides in Three Gorges reservoir area are affected by both the rainfall and the reservoir water, but their respective contribution and the laws of the landslide evolution remain unclear. In this paper, we analyzed the rainfall and water level data, and applied a varying coefficient regression model for landslide displacement prediction taking Shuping landslide and Bazimen landslide in the reservoir area as the study area. The results of experiments show that the improved varying coefficient regression model is not only more accurate than traditional linear regression model, auto-regressive Integrated moving average model and support vector mchine model, but also it can give quantitative contribution of each factor on the landslide displacement.
- Three Gorges reservoir area,
- rainfall,
- reservoir water,
- varying coefficient regression model,
- landslide displacement prediction,
- numerical models

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References(23)

References

Du, J., Yin, K.L., et al., 2009.Study of Displacement Prediction Model of Landslide Based on Response Analysis of Inducing Factors.Chinese Journal of Rock Mechanics and Engineering, 28(9):1783-1789.doi: 10.3321/j.issn:1000-6915.2009.09.007

Du, J., Yin, K.L., Lacasse, S., 2012.Displacement Prediction in Colluvial Landslides, Three Gorges Reservoir, China.Landslides, 10(2):203-218.doi: 10.1007/s10346-012-0326-8

Fan, J.Q., Huang, T., 2005.Profile Likelihood Inferences on Semiparametric Varying-Coefficient Partially Linear Models.Bernoulli, 11(6):1031-1057.doi: 10.3150/bj/1137421639

Hastie, T., Tibshirani, R., 1993.Varying-Coefficient Models.Journal of the Royal Statistical Society Series, 55(4):757-796. doi: 10.1111/insr.12029/abstract

Huang, F.M., Yin, K.L., Zhang, G.R., et al., 2015.Landslide Groundwater Level Time Series Prediction Based on Phase Space Reconstruction and Wavelet Analysis-Support Vector Machine Optimized by Pso Algorithm.Earth Science, 40(7):1254-1265 (in Chinese with English abstract). https://www.researchgate.net/publication/283124003_Landslide_groundwater_level_time_series_prediction_based_on_phase_space_reconstruction_and_wavelet_analysis-support_vector_machine_optimized_by_PSO_algorithm

Lian, C., Zeng, Z.G., Yao, W., et al., 2012.Displacement Prediction Model of Landslide Based on a Modified Ensemble Empirical Mode Decomposition and Extreme Learning Machine.Natural Hazards, 66(2):759-771.doi: 10.1007/s11069-012-0517-6

Lian, C., Zeng, Z.G., Yao, W., et al., 2013.Ensemble of Extreme Learning Machine for Landslide Displacement Prediction Based on Time Series Analysis.Neural Computing and Applications, 24(1):99-107.doi: 10.1007/s00521-013-1446-3

Lian, C., Zeng, Z.G., Yao, W., et al., 2014.Extreme Learning Machine for the Displacement Prediction of Landslide under Rainfall and Reservoir Level.Stochastic Environmental Research and Risk Assessment, 28(8):1957-1972.doi: 10.1007/s00477-014-0875-6

Lu, C.L., Kuang, C.L., Dai, W.J., et al., 2014.Extracting Seasonal Signals from Continuous GPS Time Series Based on Varying-Coefficient Regression Models.Journal of Geodesy and Geodynamics, 34(5):94-100 (in Chinese with English abstract). http://www.jgg09.com/EN/abstract/abstract10275.shtml

Lu, J., Dai, W.J., Zhang, Z.T., 2015.Modeling Dam Deformation Using Varying Coefficient Regression.Geomatics and Information Science of Wuhan University, 40(1):139-142 (in Chinese with English abstract). https://www.researchgate.net/publication/283649959_Modeling_dam_deformation_using_varying_coefficient_regression

Lu, S.Q., Yi, Q.L., Yi, W., et al., 2014.Study on Dynamic Deformation Mechanism of Landslide in Drawdown of Reservoir Water Level-Take Baishuihe Landslide in Three Gorges Reservoir Area for Example.Journal of Engineering Geology, 22(5):869-875 (in Chinese with English abstract). doi: 10.1007/s00477-016-1224-8

Luo, H.M., Tang, H.M., Zhang, G.C., et al., 2008.The Influence of Water Level Fluctuation on the Bank Landslide Stability.Earth Science, 33(5):687-692 (in Chinese with English abstract). https://www.researchgate.net/publication/289830334_The_influence_of_water_level_fluctuation_on_the_bank_landslide_stability

Mei, C.L., Wang, N., 2012.Modern Regression Analysis and Method.The Science Publishing Company, Beijing (in Chinese).

Peng, L., Niu, R.Q., Yang, Y.N., et al., 2013.Landslide Displacement Prediction Based on Kernel Principal Component Analysis and Particle Swarm Support Vector Machine.Journal of Wuhan University (Information Science Edition), 38(2):148-152(in Chinese). https://www.researchgate.net/publication/286283016_Landslide_spatial_prediction_based_on_slope_units_and_support_vector_machines

Yi, Q.L., Zeng, H.E., Huang, H.F., 2013.Reservoir Landslide Deformation Forecast Using BP Neural Network.Hydrogeology & Engineering Geology, 40(1):124-128 (in Chinese with English abstract). doi: 10.1007/s12559-012-9148-1

黄发明, 殷坤龙, 张桂荣, 等, 2015.基于相空间重构和小波分析-粒子群向量机的滑坡地下水位预测.地球科学, 40(7): 1254-1265. http://www.earth-science.net/WebPage/Article.aspx?id=3113

卢辰龙, 匡翠林, 戴吾蛟, 等, 2014.采用变系数回归模型提取GPS坐标序列季节性信号.大地测量与地球动力学, 34(5): 94-100. http://www.cnki.com.cn/Article/CJFDTOTAL-DKXB201405020.htm

卢骏, 戴吾蛟, 章浙涛, 2015.大坝变形变系数回归建模.武汉大学学报(信息科学版), 40(1): 139-142. http://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201501024.htm

卢书强, 易庆林, 易武, 等, 2014.库水下降作用下滑坡动态变形机理分析--以三峡库区白水河滑坡为例.工程地质学报, 22(5): 869-875. http://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201405016.htm

罗红明, 唐辉明, 章广成, 等, 2008.库水位涨落对库岸滑坡稳定性的影响.地球科学, 33(5): 687-692. http://www.earth-science.net/WebPage/Article.aspx?id=1689

梅长林, 王宁, 2012.近代回归分析方法.北京:科学出版社.

彭令, 牛瑞卿, 杨艳南, 等, 2013.基于核主成分分析和粒子群优化支持向量机的滑坡位移预测.武汉大学学报(信息科学版), 38(2): 148-152. http://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201302006.htm

易庆林, 曾怀恩, 黄海峰, 2013.利用BP神经网络进行水库滑坡变形预测.水文地质工程地质, 40(1): 124-128. http://www.cnki.com.cn/Article/CJFDTOTAL-SWDG201301027.htm

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Landslide Displacement Prediction Based on Varying Coefficient Regression Model in Three Gorges Reservoir Area

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