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《Hydrogeology & Engineering Geology》 2013-01
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Reservoir landslide deformation forecast using BP neural network

YI Qing-lin1,2,ZENG Huai-en1,2,HUANG Hai-feng1,2(1.Key Laboratory of Geological Hazards on Three Gorges Reservoir Area,Ministry of Education,China Three Gorges University,Yichang 443002,China;2.Engineering Research Center for Geological Hazards Prevention and Cure, Hubei province,China Three Gorges University,Yichang 443002,China)  
Landslides deformation monitoring and forecast is a very important approach to early landslide warning and forecast.The basic principle and algorithm of BP neural network are briefly introduced in this paper.With 24 sets of GPS displacement monitoring data and the corresponding cause information,i.e.reservoir level and rainfall of a reservoir landslides,the landslide deformation model is constructed using BP neural network.The late 6 sets of cause information are put into the deformation model and the forecasted deformation is obtained.The results show that the forecasted deformation has a good fit performance with the fatual surveying deformation and can reflect the overall deformation trend.The results have referrence value for landslide deformation forecast.
【Fund】: 国家自然科学基金项目(41104009);; 地球空间环境与大地测量教育部重点实验室开放基金资助项目(11-01-04);; 精密工程与工业测量国家测绘地理信息局重点实验室开放基金项目(PF2011-4)
【CateGory Index】: P642.22
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