Landslide susceptibility assessment is the problem of determining the likelihood of a landslide to occur in a particular area based on the geological and morphological properties of the area. In this study we propose a method wherein skyline operator is used to model landslides and majority voting is used to assess landslide susceptibility. Experiments conducted on a real life data set show that the proposed method achieves 83.07% classification accuracy and is superior over logistic regression, support vector machine and neural network based approaches and achieves similar results when compared to a decision trees-based model.
Landslide Susceptibility Assessment Majority Voting Skyline Operator
Birincil Dil | İngilizce |
---|---|
Konular | Bilgisayar Yazılımı, Çevre Bilimleri |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Yayımlanma Tarihi | 1 Ekim 2019 |
Gönderilme Tarihi | 7 Kasım 2018 |
Kabul Tarihi | 20 Mart 2019 |
Yayımlandığı Sayı | Yıl 2019 Cilt: 23 Sayı: 5 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.