| Summary: | 碩士 === 國立屏東科技大學 === 森林系所 === 97 === Landslides has become one disaster type of the most serious destroy on the slope lands. The way to monitoring and assessment for landslide area can help government agencies to select suitable management and plan mitigation in unstable landslide areas. This research presents a case study of landslide monitoring and assessment at Shanzongliao landslide area, Taitung County, attempt to predict slope movements using back propagation neural network (BPNN), as well as use powerful tools to model and investigate various complex and non-linear phenomena. The BPNN can performed calculation to use MATLAB program with the Levenberg-Marquardt algorithm. The data from the case study are used to train and test the developed model to enable prediction of the magnitude of the ground movements with the help of input variables that have direct physical significance. An infiltration coefficient is introduced in the network architecture apart from antecedent rainfall, rainfall intensity, slope profile, groundwater level and shear strength of soil. A four-layered back propagation neural network with an input layer, two hidden layers and one output layer is found optimal. The developed BPNN model demonstrates a promising result, and have good potential accurately for predicting the slope movement, and can offer the reference of disaster prevention and utilizing management at the steep slope.
|
|---|
