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Landslide hazards mapping using uncertain Naive Bayesian classification method
  • ISSN号:1002-8331
  • 期刊名称:《计算机工程与应用》
  • 时间:0
  • 分类:P315.9[天文地球—地震学;天文地球—固体地球物理学;天文地球—地球物理学] TP301.6[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]Key Laboratory for Geo-hazard in Loess Area, Ministry of Land and Resources (MLR), Xi'an 710086, China, [2]School of Geology Engineering and Geomatics, Chang'an University, Xi'an 710064, China, [3]Applied Science Institute, Jiangxi University of Science and Technology, Ganzhou 341000, China
  • 相关基金:Projects(41362015,51164012) supported by the National Natural Science Foundation of China; Project(2012AA061901) supported by the National High-tech Research and Development Program of China
中文摘要:

Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Na?ve Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Na?ve Bayesian classification method in Baota district of Yan’an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Na?ve Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves(AUC) in NBU and Na?ve Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.

英文摘要:

Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naive Bayesian classification method in Baota district of Yan'an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naive Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves(AUC) in NBU and Naive Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.

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期刊信息
  • 《计算机工程与应用》
  • 北大核心期刊(2014版)
  • 主管单位:中国电子科技集团公司
  • 主办单位:华北计算技术研究所
  • 主编:怀进鹏
  • 地址:北京市海淀区北四环中路211号北京619信箱26分箱
  • 邮编:100083
  • 邮箱:ceaj@vip.163.com
  • 电话:
  • 国际标准刊号:ISSN:1002-8331
  • 国内统一刊号:ISSN:11-2127/TP
  • 邮发代号:82-605
  • 获奖情况:
  • 1. 2012年首批获得中国学术文献评价中心发布的 “...,2. 2001年获得新闻出版署“中国期刊方阵双效期刊”,3. 2008年首批入选国家科技部“中国精品科技期刊...,4.2003年-2011年连续获得工业和信息化部期刊最高...
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  • 俄罗斯文摘杂志,波兰哥白尼索引,美国剑桥科学文摘,英国科学文摘数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:97887