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Modelling landslide susceptibility prediction: a review and construction of semi-supervised imbalanced theory
F Huang, H ** based on the reliability of landslide and non-landslide sample
Spatial data sampling can improve the performance in geo-spatial prediction. However,
measuring the reliability of polygon-based data in sampling process is still a challenge. In …
measuring the reliability of polygon-based data in sampling process is still a challenge. In …
Refined landslide susceptibility analysis based on InSAR technology and UAV multi-source data
C Cao, K Zhu, P Xu, B Shan, G Yang, S Song - Journal of Cleaner …, 2022 - Elsevier
Landslide susceptibility analysis at the regional scale is the focus of landslide risk
management. To obtain more accurate and guiding significance results of landslide …
management. To obtain more accurate and guiding significance results of landslide …
Risk assessment of roadway networks exposed to landslides in mountainous regions—A case study in Fengjie County, China
Landslides frequently disrupt roadway networks in mountainous regions worldwide.
Because of the relatively long roadway extension and low roadway density in mountainous …
Because of the relatively long roadway extension and low roadway density in mountainous …
Extracting historical flood locations from news media data by the named entity recognition (NER) model to assess urban flood susceptibility
Flood susceptibility assessment for identifying flood-prone areas plays a significant role in
flood hazard mitigation. Machine learning is an optional assessment method because of its …
flood hazard mitigation. Machine learning is an optional assessment method because of its …
[HTML][HTML] A hybrid data-driven approach for rainfall-induced landslide susceptibility map**: Physically-based probabilistic model with convolutional neural network
Landslide susceptibility map** (LSM) plays a crucial role in assessing geological risks.
The current LSM techniques face a significant challenge in achieving accurate results due to …
The current LSM techniques face a significant challenge in achieving accurate results due to …
Learning a deep attention dilated residual convolutional neural network for landslide susceptibility map** in Hanzhong City, Shaanxi Province, China
The analysis and evaluation of landslide susceptibility are of great significance in preventing
and managing geological hazards. Aiming at the problems of insufficient information caused …
and managing geological hazards. Aiming at the problems of insufficient information caused …
Application of Naive Bayes, kernel logistic regression and alternation decision tree for landslide susceptibility map** in Pengyang County, China
The purpose of this research is to apply and compare the performance of the three machine
learning algorithms-Naive Bayes (NB), kernel logistic regression (KLR), and alternation …
learning algorithms-Naive Bayes (NB), kernel logistic regression (KLR), and alternation …