Application of Back Propagation Neural Networks with Optimization of Genetic Algorithms to Landslide Hazard Prediction
详细信息
- 责任者：Chen Yuping (Wenhua College ; Huazhong University of Science and Technology ; Wuhan 430074 ; China) ; Yuan Zhiqiang
- 刊名：Hydrogeology and Engineering Geology
- 出版年：2012
- 卷期：39(1)
- 关键词：遗传算法 ; genetic algorithms ; BP神经网络系统 ; BP neural network system ; 滑坡 ; landslides
- 页码：p.114-119
- 图表：7 illus., 11 refs.
- 分类号：1900
- issnNo：ISSN1000-3665
- isbnNo：CN11-2202/P
摘要
///Through the use of direct-reverse DEM technology,the Changshougou valley is divided into 216 slope units,which includes 123 landslide units.After the spatial analysis of environmental factors,this paper presents a case study for landslide hazard prediction,using back-propagation artificial neural network modeling optimized by genetic algorithms.From a database of 216 landslides,120 landslides are used for training neural network models,and 96 landslides are used for the validation of landslide susceptibility.Comparing landslide presence with a susceptibility map,it is noted that the prediction accuracy of landslide occurrence is 93.02%,while the units without landslide occurrence is predicted with accuracy of 81.13%.The verification shows satisfactory agreement with accuracy of 86.46% between the susceptibility map and the landslide locations.
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