Results 161 to 170 of about 32,207 (198)

An integrated multi-hazard assessment using machine learning in the complex terrains of Northern Pakistan. [PDF]

Sci Rep
Khan MI, Shafique M, Khattak GA, Yahya A, Badruddin IA.   +4 more
europepmc   +1 more source

Landslide Susceptibility Evaluation Integrating Machine Learning and SBAS-InSAR-Derived Deformation Characteristics: A Case Study of Yining County, Xinjiang. [PDF]

Sensors (Basel)
Ma T, Yi X, Ci H, Wang R, Yang H, Yan Z.
europepmc   +1 more source

Assessment of landslide hazard under specific rainfall scenarios based on a hybrid CNN-TRIGRS and matrix approach: a case study of Meishan Town, Zhejiang Province, China. [PDF]

Sci Rep
Wang Z, Wang Z, Shi F, Zhang X, Bi D, Qu L.   +5 more
europepmc   +1 more source

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Review on landslide susceptibility mapping using support vector machines

Catena, 2018
Landslides are natural phenomena that can cause great loss of life and damage to property. A landslide susceptibility map is a useful tool to help with land management in landslide-prone areas.
Yu Huang
exaly   +2 more sources

A comprehensive review of machine learning‐based methods in landslide susceptibility mapping

Geological Journal, 2023
Landslide susceptibility mapping (LSM) has been widely used as an important reference for development and construction planning to mitigate the potential social‐eco impact caused by landslides.
Songlin Liu, Luqi Wang, Wenpeng Zhang, Yuwei He, Samui Pijush   +4 more
semanticscholar   +1 more source

Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing

Geological Journal, 2023
Landslide susceptibility analysis can provide theoretical support for landslide risk management. However, some susceptibility analyses are not sufficiently interpretable. Moreover, the accuracy of many research methods needs to be improved.
Wen-ge Zhang, Yuwei He, Luqi Wang, Songlin Liu, Xuanyu Meng   +4 more
semanticscholar   +1 more source

Landslide Susceptibility Mapping using CNN

Journal of Applied Science, Engineering, Technology and Management
Landslide Susceptibility Mapping (LSM) is crucial for identifying regions at risk of landslides, which aids in disaster risk reduction and sustainable land-use planning.
Anu Mary Charly, S. Mohan, Lekshmy Raghavan   +2 more
semanticscholar   +1 more source

Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost)

The Arabian journal for science and engineering, 2022
T. Kavzoglu, A. Teke
semanticscholar   +1 more source

Comparative analysis of multiple conventional neural networks for landslide susceptibility mapping

Natural Hazards, 2022
Bilal Aslam, A. Zafar, Umer Khalil
semanticscholar   +1 more source