Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks-Reference-Cited by-同舟云学术

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

Published:2021-03 Issue:2 Volume:12 Page:625-637
ISSN:1674-9871
Container-title:Geoscience Frontiers
language:en
Short-container-title:Geoscience Frontiers

Author:

Al-Najjar Husam A.H.,Pradhan Biswajeet

Funder

University of Technology Sydney

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences

Reference72 articles.

1. Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia;Aditian;Geomorphology,2018

2. Comparison of major statistical methods and their combination using matrix validation for landslide susceptibility mapping;Akbar;Lowland Technol. Int.,2018

3. Landslide susceptibility mapping using an automatic sampling algorithm based on two level random sampling;Aktas;Comput. Geosci.,2019

4. Conditioning factor determination for mapping and prediction of landslide susceptibility using machine learning algorithms;Al-Najjar,2019

5. Hazard zoning for spatial planning using GIS-based landslide susceptibility assessment: a new hybrid integrated data-driven and knowledge-based model;Ashournejad;Arabian Journal of Geosciences,2019

Cited by 118 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A new integrated intelligent computing paradigm for predicting joints shear strength;Geoscience Frontiers;2024-11

2. A hybrid approach combining physics-based model with extreme value analysis for temporal probability of rainfall-triggered landslide;Landslides;2024-09-14

3. Hazard Susceptibility Mapping with Machine and Deep Learning: A Literature Review;Remote Sensing;2024-09-11

4. Investigating landslide data balancing for susceptibility mapping using generative and machine learning models;Landslides;2024-09-05

5. Landslide susceptibility mapping using an integration of different statistical models for the 2015 Nepal earthquake in Tibet;Geomatics, Natural Hazards and Risk;2024-08-30