长江科学院院报 ›› 2013, Vol. 30 ›› Issue (5): 38-41.DOI: 10.3969/j.issn.1001-5485.2013.05.09

• 工程安全与灾害防治 • 上一篇    下一篇

滑坡监测动态数据挖掘方法研究

段功豪,牛瑞卿   

  1. 中国地质大学 地球物理与空间信息学院 武汉 430074
  • 收稿日期:2012-04-30 修回日期:2013-04-28 出版日期:2013-04-28 发布日期:2013-04-28
  • 作者简介:段功豪(1988-),男,湖北武汉人,硕士研究生,主要从事遥感影像数据挖掘、海量影像数据库系统研究,(电话)15071278896(电子信箱)vipdgh@163.com。
  • 基金资助:
    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)

A Method of Dynamic Data Mining for Landslide Monitoring Data

DUAN Gong-hao,NIU Rui-qing   

  1. Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China
  • Received:2012-04-30 Revised:2013-04-28 Online:2013-04-28 Published:2013-04-28

摘要: 为有效挖掘海量、动态的滑坡监测数据中的有用信息及规律,提出了一种利用Oracle触发器监测数据的挖掘方法。以八字门滑坡为研究对象,结合ARIMA模型对累积位移进行预测,利用触发器精炼监测数据和优化模型参数,提升预测模型的拟合精度。实验结果表明,该方法能有效改良传统静态数据挖掘结果,有助于人们认识到动态数据挖掘在滑坡灾害监测中的价值。

关键词: 动态数据挖掘 , 滑坡监测 , Oracle触发器 , ARIMA

Abstract: To efficiently excavate the knowledge from substantial and dynamic landslide monitoring data,we put 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.

Key words: dynamic data mining , landslide monitoring , Oracle trigger , ARIMA

中图分类号: