Prediction of Characteristic Parameters of the Surge by Landslides

Abstract:

Instability of landslides will lead to high-speed of rock and soil into the water, sparking a huge surge, causing significant harm to residents and infrastructure of coastal areas. With regard to the surge by landslide, the climbing height and the dynamic pressure are dominant characteristic parameters of concern, which influence the scope and extent of damage. The paper selected five important factors which influence characteristic parameters, that are time into water, sliding volume, angle into water, climbing angle, and water depth, based on simulation and MATLAB, established the BP neural network model of the characteristic parameters. Through training the network at various hidden node, the optimal training network has been gained, characteristic parameters at four groups of sample data have been predicted and verified respectively, and the best forecasting network can be selected as the predicting network.

• Periodical: Applied Mechanics and Materials (Volumes 448-453)
• Pages: 1051-1056
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.448-453.1051
• Online since: October 2013
• Authors: Hong Ji*, Hu Si, Tao Xia
• Keywords: BP Neural Network (BPNN), Landslide, MATLAB, Maximum Climbing Height, Maximum Dynamic Pressure, Parameter Prediction, Surge

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