Reservoir landslide deformation forecast using BP neural network

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.