Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms

Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms

Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices, and can cause social upheaval and loss of life. As a result, many scientists study the phenomenon, and some of them have focused on producing landslide susceptibility maps that can be used by land-use manage...

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Bibliographic Details
Main Authors: Viet-Ha Nhu, Ataollah Shirzadi, Himan Shahabi, Sushant K. Singh, Nadhir Al-Ansari, John J. Clague, Abolfazl Jaafari, Wei Chen, Shaghayegh Miraki, Jie Dou, Chinh Luu, Krzysztof Górski, Binh Thai Pham, Huu Duy Nguyen, Baharin Bin Ahmad
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Shallow landslide
artificial intelligence
prediction accuracy
logistic model tree
goodness-of-fit
Iran
Online Access:https://www.mdpi.com/1660-4601/17/8/2749

Internet

https://www.mdpi.com/1660-4601/17/8/2749

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