Landslide susceptibility assessment at the Wuning area, China: a comparison between multi-criteria decision making, bivariate statistical and machine learning methods
By Haoyuan Hong, Himan Shahabi, Ataollah Shirzadi, Wei Chen, Kamran Chapi, Baharin bin Ahmad, Majid Shadman Roodposhti, arastoo yari hesar, Yingying Tian, D. Tien Bui. Natural Hazards, 2018
121 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Management, Monitoring, Policy and Law, Soil Science
View Paper: https://www.semanticscholar.org/paper/7ba724647bf67ee5987877cc18e9e115862e5b9a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Global and Planetary Change
- Binh Thai Pham
- Ataollah Shirzadi
- Himan Shahabi
- D. Tien Bui
- Baharin bin Ahmad
- Saro Lee
- Marten Geertsema
- John J. Clague
In Management, Monitoring, Policy and Law
- Binh Thai Pham
- Himan Shahabi
- Baharin bin Ahmad
- Ataollah Shirzadi
- D. Tien Bui
- Saro Lee
- Marten Geertsema
- Dawood Talebpour Asl
In Soil Science
Citations in the corpus
- New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed (2019, methodology): “…in recent years include logistic regression [7–9], multivariate regression [10–12], discriminant analysis [13,14], certainty factor [15,16], index or entropy (IOE) [17,18], spatial multi-criteria evaluation (SMCE) [19], statistical index [20,21], and analytic hierarchy processes [22,23].”