Landslide displacement dynamic prediction method based on multiple influence factors
A technology of impact factors and dynamic prediction, applied in special data processing applications, biological neural network models, instruments, etc., can solve problems such as information cannot be preserved, and achieve accurate prediction results
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[0093] 1) if image 3 As shown, the time series curves of cumulative displacement of landslides at 5 monitoring points (GXT1, GXT2, GXT3, GXT4, GXT5) from 2003 to 2007. Looking at the 5 monitoring points, it can be seen that the cumulative deformation and displacement of landslides fluctuate more from May to November each year. large, showing an overall increasing trend; Figure 4 As shown, it is the accumulated deformation displacement time and monthly rainfall data of the GXT4 monitoring point at the front edge of the landslide. It can be seen from the figure that in the rainy season, the deformation displacement of the landslide shows a nonlinear increase trend with the increase of rainfall intensity. For example, in 2004 1 From April to April, the total rainfall of the landslide was 246.8mm, the corresponding maximum increment of deformation displacement was 2.037mm, and the displacement rate was 0.679mm / month, but from May to November, the maximum increment of landslide d...
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