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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/53859/1/Spatial%20prediction%20of%20landslide%20hazard%20at%20the%20Luxi%20area.pdf http://psasir.upm.edu.my/id/eprint/53859/ https://link.springer.com/article/10.1007/s12665-015-4866-9 |
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