期刊
LANDSLIDES
卷 14, 期 1, 页码 311-322出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s10346-016-0693-7
关键词
Data mining; Two-step cluster; Apriori algorithm; Majiagou landslide; Displacement; Water level fluctuation; Rainfall
资金
- National Basic Research Program 973 Project of the Ministry of Science and Technology of the People's Republic of China [2011CB710604, 2011CB710606]
- Key National Natural Science Foundation of China [41230637]
- National Natural Science Foundation of China [41572279, 41272305, 41102195]
- China Postdoctoral Science Foundation [2012M521500, 2014T70758]
- Hubei Provincial Natural Science Foundation of China [2014CFB901]
In this study, a data mining approach is proposed to investigate the hydrological causes of the Majiagou landslide, located in the Three Gorges Reservoir in China. It is possible to determine the cause-and-effect relationships between hydrological parameters and landslide movement. The data mining approach consists of two steps: first, hydrological indicators and landslide movements are discretized using the two-step cluster analysis; second, the association rule mining with the Apriori algorithm is employed to identify the contribution of each hydrological parameter to landslide movement. The results obtained suggest that deformation and later failure occurred first at the toe of the landslide and progressed upslope due to rising water level in the reservoir, prolonged heavy rainfall, and rapid drawdown in the reservoir. The proposed novel use of field data and data mining has the potential for providing procedures and solutions for an effective interpretation of landslide monitoring data.
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