Assessment of debris flow hazards using a Bayesian Network

CORC > 地理科学与资源研究所 > 中国科学院地理科学与资源研究所 > 自然资源与环境安全研究部 > 环境修复与资源工程研究室 > SCI/SSCI期刊论文

	Assessment of debris flow hazards using a Bayesian Network
	Jiang D.; Zhuang D. F.; Ren H. Y.
	2012
关键词	Debris flow hazard Bayesian Network Hazard assessment Chinese mainland shallow landslide susceptibility artificial neural-networks hong-kong natural slopes lantau island water-quality gis prediction mountains inventory
英文摘要	Comprehensive assessment of debris flow hazard risk is challenging due to the complexity and uncertainties of various related factors. A reasonable and reliable assessment should be based on sufficient data and realistic approaches. This study presents a novel appeoach for assessing debris flow hazard risk using BN (Bayesian Network) and domain knowledge. Based on the records of debris flow hazards and geomorphological/environmental data for the Chinese mainland, approaches based on BN, SVM (Support Vector Machine) and ANN (Artificial Neural Network) were compared. BN provided the highest values of hazard detection probability, precision, and AUC (area under the receiver operating characteristic curve). The BN model is useful for mapping and assessing debris flow hazard risk on a national scale. (C) 2012 Elsevier B.V. All rights reserved.
出处	Geomorphology
卷	171
页	94-100
收录类别	SCI
语种	英语
ISSN号	0169-555X
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/30824]
专题	资源利用与环境修复重点实验室_资源地理与国土资源研究室_SCI/SSCI期刊论文中国科学院地理科学与资源研究所
推荐引用方式 GB/T 7714	Jiang D.,Zhuang D. F.,Ren H. Y.. Assessment of debris flow hazards using a Bayesian Network. 2012.