Evaluation of Highway Slope Failure Using Artificial Neural Networks

• Main Authors: Yuh-Pin Lu, 盧育聘
• Other Authors: Tsong-Lin Lee
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/19953899993696549321

碩士 === 立德管理學院 === 資源環境研究所 === 91 === In recent years, the highway slope failure has been widely studied by geotechnical engineers. However, Conventional investigations for determining slope failure have focused on the linear relationships among many factors, such as slope angle, slope height, material, construction, rainfall, earthquake and so on. In fact, this problem is still a complex nonlinear relationship. This paper presents an application of the artificial neural network for assessing the slope failure using these factors. On site slope failure data at the highways of Taiwan 20 (South-Cross Highway) and the highways of Taiwan 18 (A-Li-San Highway) were used to test the performance of the artificial neural network model. The results indicate that the artificial neural network can be efficiently estimated slope failure potential using the major factors.