Citation: | DING Geyuan. DISPLACEMENT PREDICTION OF THE ZHUJIADIAN LANDSLIDE WITH OUTLIERS[J]. JOURNAL OF MECHANICAL ENGINEERING, 2020, 28(1): 132-140. doi: 10.13544/j.cnki.jeg.2019-235 |
Dong D M, Liang Y, Wang L Q, et al. 2017. Displacement prediction method based on ensemble empirical mode decomposition and support vector machine regression—a case of landslides in Three Gorges Reservoir area[J]. Rock and Soil Mechanics, 38(12): 366-3669.
|
Hu X L, Zhang M, Sun M J, et al. 2015. Deformation characteristics and failure mode of the Zhujiadian landslide in the Three Gorges Reservoir, China[J]. Bulletin of Engineering Geology and the Environment, 74(1): 1-12. doi: 10.1007/s10064-013-0552-x
|
Lei D X, Yi W. 2018. Prediction and forecast of landslide displacement based on ARIMA model: case of Wangjiapo landslide in Three Gorges Reservoir area[J]. Yangtze River, 49 (21): 56-60, 83. http://d.old.wanfangdata.com.cn/Periodical/rmcj201821011
|
Li C D, Tang H M, Hu X L, et al. 2009. Landslide prediction based on wavelet analysis and cusp catastrophe[J]. Journal of Earth Science, 20(6): 971. doi: 10.1007/s12583-009-0082-4
|
Li J, Zhang Z J, Hiu R Q, et al. 2016. Prediction of landslide displacement based on ARIMA-MC model[J]. Computer Engineering and Applications, 52(7): 215-221. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjgcyyy201607040
|
Li S W, Li Y C. 2015. Landslide displacement prediction based on ARIMA model[J]. Journal of Chengdu University(Natural Science Edition), 34(4): 421-424. http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb201704016
|
Ma J W. 2016. Rvolution characteristics of multiple physics-based parameters and data mining technology for progressive landslides[J]. Wuhan: China University of Geosciences(Wuhan).
|
Ma J W, Tang H M, Liu X, et al. 2017. Establishment of a deformation forecasting model for a step-like landslide based on decision tree C5.0 and two-step cluster algorithms: a case study in the Three Gorges Reservoir area, China[J]. Landslides, 14(3): 1275-1281. doi: 10.1007/s10346-017-0804-0
|
Miao F S, Wu Y P, Xie Y H, et al. 2017. Prediction of landslide displacement with step-like behavior based on multialgorithm optimization and a support vector regression model[J]. Landslides, 15(3): 1-14. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=04ecaca2e44c7cf99ebf484dc17fa242
|
Miao F S, Wu Y P, Xie Y H, et al. 2016. Displacement prediction of baishuihe landslide based on multi algorithm optimization and SVR model[J]. Journal of Engineering Geology, 24(6): 1136-1144. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gcdzxb201606016
|
Tan F L, Hu X L, He C C, et al. 2018. Identifying the main control factors for different deformation stages of landslide[J]. Geotechnical and Geological Engineering, 36(1): 469-482. doi: 10.1007/s10706-017-0340-7
|
Tan F L. 2018. Evaluation method for dynamic stability of landslide stabilizing pile system with different evolution modes[J]. Wuhan: China University of Geosciences(Wuhan).
|
Xu F, Wang Y, Du J, et al. 2011. Study of displacement prediction model of landslide based on time series analysis[J]. Chinese Journal of Rock Mechanics and Engineering, 30(4): 746-751.
|
Yan H, Li S H, Wu L Z. 2019. Landslide displacement prediction based on multiple data-driven model methods[J]. Journal of Engineering Geology, 27(2): 459-465. http://d.old.wanfangdata.com.cn/Periodical/gcdzxb201902028
|
Zhao H, Shao S H, Xie D P. 2004. Examination method for qutlier of analytical data[J]. Journal of Zhoukou Teachers College, 21(5): 70-71. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zksfgdzkxxxb200405021
|
Zhou C, Yin K L, Cao Y, et al. 2016. Application of time series analysis and PSO-SVM model in predicting the Bazimen landslide in the Three Gorges Reservoir, China[J]. Engineering Geology, 204 : 108-120. doi: 10.1016/j.enggeo.2016.02.009
|
Zhu J X, Bao Y T, Li Z. 2018. Discussion on the method for testing and treating outliers[J]. University Chemistry, 33(8): 58-65. http://d.old.wanfangdata.com.cn/Periodical/dxhx201808012
|
邓冬梅, 梁烨, 王亮清, 等. 2017.基于集合经验模态分解与支持向量机回归的位移预测方法:以三峡库区滑坡为例[J].岩土力学, 38(12): 3660-3669. http://d.old.wanfangdata.com.cn/Periodical/ytlx201712035
|
雷德鑫, 易武. 2018.基于ARIMA时间序列模型的滑坡位移预测预报——以三峡库区王家坡滑坡为例[J].人民长江, 49 (21): 60-64, 87. http://www.cnki.com.cn/Article/CJFDTotal-RIVE201821011.htm
|
李炯, 张志军, 牛瑞卿, 等. 2016.基于ARIMA-MC模型的滑坡位移预测[J].计算机工程与应用, 52(7): 215-221. doi: 10.3778/j.issn.1002-8331.1404-0187
|
李首位, 李益陈. 2015.基于ARIMA模型的滑坡位移预测[J].成都大学学报(自然科学版), 34(4): 421-424. doi: 10.3969/j.issn.1004-5422.2015.04.026
|
马俊伟. 2016.渐进式滑坡多场信息演化特征与数据挖掘研究[D].武汉: 中国地质大学(武汉). http://cdmd.cnki.com.cn/Article/CDMD-10491-1016312151.htm
|
苗发盛, 吴益平, 谢媛华, 等. 2016.基于多算法参数优化与SVR模型的白水河滑坡位移预测[J].工程地质学报, 24(6): 1136-1144. doi: 10.13544/j.cnki.jeg.2016.06.013
|
谭福林. 2018.基于不同演化模式的滑坡-抗滑桩体系动态稳定性评价方法研究[D].武汉: 中国地质大学(武汉). http://cdmd.cnki.com.cn/Article/CDMD-10491-1018817136.htm
|
王玉荣. 2004. ARIMA模型在我国出口贸易预测中的应用[J].统计与决策, (4): 33-34. doi: 10.3969/j.issn.1002-6487.2004.04.019
|
徐峰, 汪洋, 杜娟, 等. 2011.基于时间序列分析的滑坡位移预测模型研究[J].岩石力学与工程学报, 30(4): 746-751. http://d.old.wanfangdata.com.cn/Periodical/yslxygcxb201104012
|
鄢好, 李绍红, 吴礼舟. 2019.联合多种数据驱动建模方法的滑坡位移预测研究[J].工程地质学报, 27(2): 459-465. doi: 10.13544/j.cnki.jeg.2017-485
|
赵辉, 邵素华, 谢东坡. 2004.分析数据中离群值的处理方法[J].周口师范学院学报, 21(5): 70-71. doi: 10.3969/j.issn.1671-9476.2004.05.021
|
中华人民共和国行业标准编写组. 2008.数据的统计处理和解释正态样本离群值的判断和处理(GB/T 4883-2008)[S].北京: 中国标准出版社.
|
朱嘉欣, 包雨恬, 黎朝. 2018.数据离群值的检验及处理方法讨论[J].大学化学, 33 (8): 58-65. http://d.old.wanfangdata.com.cn/Periodical/dxhx201808012
|