[HTML][HTML] Landslide susceptibility map** using machine learning algorithms and comparison of their performance at Abha Basin, Asir Region, Saudi Arabia

AM Youssef, HR Pourghasemi - Geoscience Frontiers, 2021 - Elsevier
The current study aimed at evaluating the capabilities of seven advanced machine learning
techniques (MLTs), including, Support Vector Machine (SVM), Random Forest (RF) …

A spatially explicit deep learning neural network model for the prediction of landslide susceptibility

D Van Dao, A Jaafari, M Bayat, D Mafi-Gholami, C Qi… - Catena, 2020 - Elsevier
With the increasing threat of recurring landslides, susceptibility maps are expected to play a
bigger role in promoting our understanding of future landslides and their magnitude. This …
Y Wang, Z Fang, M Wang, L Peng, H Hong - Computers & Geosciences, 2020 - Elsevier
This paper aims to use recurrent neural networks (RNNs) to perform landslide susceptibility
map** in Yongxin County, China. The two main contributions of this study are summarized …
Landslides present a substantial risk to human lives, the environment, and infrastructure.
Consequently, it is crucial to highlight the regions prone to future landslides by examining …

GIS based hybrid computational approaches for flash flood susceptibility assessment

BT Pham, M Avand, S Janizadeh, TV Phong… - Water, 2020 - mdpi.com
Flash floods are one of the most devastating natural hazards; they occur within a catchment
(region) where the response time of the drainage basin is short. Identification of probable …

GIS-based landslide susceptibility map** using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh

MS Chowdhury, MN Rahman, MS Sheikh, MA Sayeid… - Heliyon, 2024 - cell.com
The frequency of landslides and related economic and environmental damage has
increased in recent decades across the hilly areas of the world, no exception is Bangladesh …

[HTML][HTML] Flash flood susceptibility map** using a novel deep learning model based on deep belief network, back propagation and genetic algorithm

H Shahabi, A Shirzadi, S Ronoud, S Asadi, BT Pham… - Geoscience …, 2021 - Elsevier
Flash floods are responsible for loss of life and considerable property damage in many
countries. Flood susceptibility maps contribute to flood risk reduction in areas that are prone …

[HTML][HTML] Utilizing hybrid machine learning and soft computing techniques for landslide susceptibility map** in a drainage basin

Y Mao, Y Li, F Teng, AKS Sabonchi, M Azarafza… - Water, 2024 - mdpi.com
The hydrological system of thebasin of Lake Urmia is complex, deriving its supply from a
network comprising 13 perennial rivers, along withnumerous small springs and direct …

A comparison among fuzzy multi-criteria decision making, bivariate, multivariate and machine learning models in landslide susceptibility map**

QB Pham, Y Achour, SA Ali, F Parvin… - … , Natural Hazards and …, 2021 - Taylor & Francis
Landslides are dangerous events which threaten both human life and property. The study
aims to analyze the landslide susceptibility (LS) in the Kysuca river basin, Slovakia. For this …

Assessing drought vulnerability using geospatial techniques in northwestern part of Bangladesh

MAA Hoque, B Pradhan, N Ahmed - Science of the Total Environment, 2020 - Elsevier
Drought is a damaging and costly natural disaster that frequently affects many climatic
regions in the world. A multi-criteria-based approach for integrated spatial drought …