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A platform for research: civil engineering, architecture and urbanism
Analysis of Landslide Stability Based on Neural Network
A nonlinear method was applied in the stability study of landslides due to the highly nonlinear feature of landslides stability. Based on the data collected as research samples, we selected six influence factors as the indicators of slope stability, including the average slope, slope of the invading front, sliding surface slope, the maximum annual average daily rainfall, the recent slide situation and human engineering activities. Through the comprehensive analysis of landslides stability with BP neural network method, we established a novel nonlinear analysis model. And from the work we may conclude that the landslide stability analysis model is of profound technical meaning with accuracy over 95%.
Analysis of Landslide Stability Based on Neural Network
A nonlinear method was applied in the stability study of landslides due to the highly nonlinear feature of landslides stability. Based on the data collected as research samples, we selected six influence factors as the indicators of slope stability, including the average slope, slope of the invading front, sliding surface slope, the maximum annual average daily rainfall, the recent slide situation and human engineering activities. Through the comprehensive analysis of landslides stability with BP neural network method, we established a novel nonlinear analysis model. And from the work we may conclude that the landslide stability analysis model is of profound technical meaning with accuracy over 95%.
Analysis of Landslide Stability Based on Neural Network
Advanced Materials Research ; 374-377 ; 2346-2351
2011-10-24
6 pages
Article (Journal)
Electronic Resource
English
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