[HTML][HTML] Landslide susceptibility map** using machine learning: A literature survey

M Ado, K Amitab, AK Maji, E Jasińska, R Gono… - Remote Sensing, 2022 - mdpi.com
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …

Land use and land cover as a conditioning factor in landslide susceptibility: a literature review

R Pacheco Quevedo, A Velastegui-Montoya… - Landslides, 2023 - Springer
Landslide occurrence has become increasingly influenced by human activities. Accordingly,
changing land use and land cover (LULC) is an important conditioning factor in landslide …

Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment

DT Bui, P Tsangaratos, VT Nguyen, N Van Liem… - Catena, 2020 - Elsevier
The main objective of the current study was to introduce a Deep Learning Neural Network
(DLNN) model in landslide susceptibility assessments and compare its predictive …

[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility map**

L Lv, T Chen, J Dou, A Plaza - … Journal of Applied Earth Observation and …, 2022 - Elsevier
Landslides are highly hazardous geological disasters that can potentially threaten the safety
of human life and property. As a result, landslide susceptibility map** (LSM) plays an …

Machine learning based wildfire susceptibility map** using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey

MC Iban, A Sekertekin - Ecological Informatics, 2022 - Elsevier
In recent years, the number of wildfires has increased all over the world. Therefore, map**
wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire …

GIS-based comparative assessment of flood susceptibility map** using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and …

SA Ali, F Parvin, QB Pham, M Vojtek, J Vojteková… - Ecological …, 2020 - Elsevier
Flood is a devastating natural hazard that may cause damage to the environment
infrastructure, and society. Hence, identifying the susceptible areas to flood is an important …

[HTML][HTML] GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

SA Ali, F Parvin, J Vojteková, R Costache, NTT Linh… - Geoscience …, 2021 - Elsevier
Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …

A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility map**

Z Fang, Y Wang, L Peng, H Hong - International Journal of …, 2021 - Taylor & Francis
This study introduces four heterogeneous ensemble-learning techniques, that is, stacking,
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …

A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

W Chen, X **_using_optimized_PSO-ANN_technique/links/5bfd32fd92851c78dfae8b8a/Modification-of-landslide-susceptibility-map**-using-optimized-PSO-ANN-technique.pdf" data-clk="hl=cs&sa=T&oi=gga&ct=gga&cd=9&d=17129468966515747132&ei=9uqtZ573DoC96rQP29mI6AY" data-clk-atid="PKk_7EQZuO0J" target="_blank">[PDF] researchgate.net

Modification of landslide susceptibility map** using optimized PSO-ANN technique

H Moayedi, M Mehrabi, M Mosallanezhad… - Engineering with …, 2019 - Springer
In the present study, we applied artificial neural network (ANN) optimized with particle
swarm optimization (PSO) for the problem of landslide susceptibility map** (LSM) …