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Landslide Susceptibility Mapping with Data Mining Methods—a Case Study from Maily-Say, Kyrgyzstan
Braun, A.; Fernandez-Steeger, T.; Havenith, Hans-Balder et al.
2015In Engineering Geology for Society and Territory - Volume 2: Landslide Processes
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Abstract :
[en] Abstract: Multiple factors, such as geology, high mountain topography, seismic activity, climatic conditions and mining activities cause significant landslide hazard in the region around Maily-Say, Kyrgyzstan. To assess the landslide susceptibility a database containing landslide information and geological, morphological and hydrological parameters associated with landslide occurrence was established and analyzed with different data mining algorithms. The most promising results were achieved with an Artificial Neural ...
Disciplines :
Earth sciences & physical geography
Author, co-author :
Braun, A.
Fernandez-Steeger, T.
Havenith, Hans-Balder  ;  Université de Liège - ULiège > Département de géologie > Géologie de l'environnement
Torgoev, A.
Language :
English
Title :
Landslide Susceptibility Mapping with Data Mining Methods—a Case Study from Maily-Say, Kyrgyzstan
Publication date :
2015
Event name :
XII IAEG Congress, Torino 2014
Event date :
September 2014
Audience :
International
Main work title :
Engineering Geology for Society and Territory - Volume 2: Landslide Processes
Publisher :
Springer
Pages :
995-998
Peer reviewed :
Peer reviewed
Available on ORBi :
since 18 October 2014

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