articleTop 1% cited
Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS
Journal of Hydrology · 2014 · Vol. 512 · pp. 332–343
Mahyat Shafapour Tehrany✉(Universiti Putra Malaysia)Biswajeet Pradhan(Universiti Putra Malaysia)Mustafa Neamah Jebur(Universiti Putra Malaysia)
Flood Risk Assessment and ManagementHydrology and Watershed Management StudiesHydrology and Drought AnalysisSupport vector machineTopographic Wetness IndexKernel (algebra)Polynomial kernelFlood mythRadial basis function kernelBivariate analysisComputer scienceArtificial intelligenceMathematics
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References
Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS
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Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China
Geomorphology · 2008 · 594 citations
Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA
Geomorphology · 2009 · 417 citations
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Support-Vector Networks
Machine Learning · 1995 · 32,108 citations
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Machine Learning · 1995 · 39,987 citations
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