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《Journal of Yangtze River Scientific Research Institute》 2013-05
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A Method of Dynamic Data Mining for Landslide Monitoring Data

DUAN Gong-hao,NIU Rui-qing(Institute of Geophysics and Geomatics,China University of Geosciences,Wuhan 430074,China)  
To efficiently excavate the knowledge from substantial and dynamic landslide monitoring forward a data mining approach using oracle trigger to monitor data.In order to improve the fitting precision of forecasting model,the time series model ARIMA(Autoregressive Integrated Moving Average Model) was employed to forecast the accumulative displacement and the Oracle trigger was used to refine the monitoring data and optimize the model parameter.Bazimen landslide was taken as a case study.The results indicate that the method improves the mining result of traditional static data and helps people to realize the value of dynamic data in landslide prevention.
【Fund】: 国家973计划资助项目(2011CB710601);; 国家863计划资助项目(2012AA121303);; 国土资源部重大科学研究项目(SXKY3-3-2)
【CateGory Index】: P642.22
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