Spatial prediction of landslide hazard at the Luxi area (China) using support vector machines

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Spatial prediction of landslide hazard at the Luxi area (China) using support vector machines

The main objective of this study is to investigate the potential application of GIS-based Support Vector Machines (SVM) with four kernel functions, i.e., radial basis function (RBF), polynomial (PL), sigmoid (SIG), and linear (LN) for landslide susceptibility mapping at Luxi city in Jiangxi province...

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Bibliographic Details
Main Authors:	Hong, Haoyuan, Pradhan, Biswajeet, Jebur, Mustafa Neamah, Bui, Dieu Tien, Xu, Chong, Akgun, Aykut
Format:	Article
Language:	English
Published:	Springer 2016
Online Access:	http://psasir.upm.edu.my/id/eprint/53859/ http://psasir.upm.edu.my/id/eprint/53859/1/Spatial%20prediction%20of%20landslide%20hazard%20at%20the%20Luxi%20area.pdf

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