Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree
Preparation of landslide susceptibility maps is considered as the first important step in landslide risk assessments, but these maps are accepted as an end product that can be used for land use planning. The main objective of this study is to explore some new state-of-the-art sophisticated machine l...
保存先:
| 主要な著者: | , , , , |
|---|---|
| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Springer
2016
|
| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/53858/1/Spatial%20prediction%20models%20for%20shallow%20landslide%20hazards.pdf http://psasir.upm.edu.my/id/eprint/53858/ https://link.springer.com/article/10.1007/s10346-015-0557-6 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|