Abstract
This paper adopts three models including the logistic regression (LR), support vector machine (SVM), and random forest (RF) to study the susceptibility distribution rule of susceptibility distribution of earthquakes induced landslides. The Area Under the Receiver Operating Characteristic (ROC) curve (AUC) and Ratio were used for evaluating the model’s accuracy and mapping availability susceptibility assessment. The result shows that RF has the best performance in the susceptibility assessment of earthquake-induced landslides in the Lushan region of China.
Highlights
The logistic regression (LR) and random forest (RF) models were the two most commonly used models in studies for that they were effective in mapping landslide susceptibility, and currently, the support vector machine (SVM) are relatively mature in landslides susceptibility assessment
The LR and RF models were the two most commonly used models in studies for that they were effective in mapping landslide susceptibility, and currently, the SVM are relatively mature in landslides susceptibility assessment
The result reveals that RF has the best prediction the Environment. 74(2)
Summary
The LR and RF models were the two most commonly used models in studies for that they were effective in mapping landslide susceptibility, and currently, the SVM are relatively mature in landslides susceptibility assessment. The RF, LR and SVM models were selected in this study to develop earthquake-triggered landslides susceptibility models in Lushan[1]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
