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Prediction of Landslide Using Artificial Neural Network Model  

홍원표 (중앙대학교 공과대학 건설환경공학과)
김원영 (한국지질자원연구원 지질환경재해연구부)
송영석 (한국지질자원연구원 지질환경재해연구부)
임석규 (중앙대학교 대학원 토목공학과)
Publication Information
Journal of the Korean Geotechnical Society / v.20, no.8, 2004 , pp. 67-75 More about this Journal
Abstract
The landslide is one of the most significant natural disasters, which cause a lot of loss of human lives and properties. The landslides in natural slopes generally occur by complicated problems such as soil properties, topography, and geology. Artificial Neural Network (ANN) model is efficient computing technique that is widely used to solve complicated problems in many research fields. In this paper, the ANN model with application of error back propagation method was proposed for estimation of landslide hazard in natural slope. This model can evaluate the possibility of landslide hazard with two different approaches: one considering only soil properties; the other considering soil properties, topography, and geology. In order to evaluate reasonably the landslide hazard, the SlideEval (Ver, 1.0) program was developed using the ANN model. The evaluation of slope stability using the ANN model shows a high accuracy. Especially, the prediction of landslides using the ANN model gives more stable and accurate results in the case of considering such factors as soil, topographic and geological properties together. As a result of comparison with the statistical analysis(Korea Institute of Geosciences and Mineral Resources, 2003), the analysis using the ANN model is approximately equal to the statistical analysis. Therefore, the SlideEval (Ver. 1.0) program using ANN model can predict landslides hazard and estimate the slope stability.
Keywords
Artificial neural network model; Error back propagation method; Geology; Landslides hazard; Soil properties; Topography;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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