[HTML][HTML] A systematic review of trustworthy artificial intelligence applications in natural disasters

AS Albahri, YL Khaleel, MA Habeeb, RD Ismael… - Computers and …, 2024 - Elsevier
Artificial intelligence (AI) holds significant promise for advancing natural disaster
management through the use of predictive models that analyze extensive datasets, identify …

[PDF][PDF] A comprehensive review of the recent advancement in integrating deep learning with geographic information systems

A Raihan - Research Briefs on Information and Communication …, 2023 - researchgate.net
The integration of deep learning (DL) techniques with geographical information system (GIS)
offers a promising avenue for gaining novel insights into environmental phenomena by …

GIS-based landslide susceptibility mapping 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 …

Artificial neural network approaches for disaster management: A literature review

S Guha, RK Jana, MK Sanyal - International Journal of Disaster Risk …, 2022 - Elsevier
Disaster management (DM) is one of the leading fields that deal with the humanitarian
aspects of emergencies. The field has attracted researchers because of its ever-increasing …

Geomorphic and sedimentary effects of modern climate change: current and anticipated future conditions in the western United States

AE East, JB Sankey - Reviews of Geophysics, 2020 - Wiley Online Library
Hydroclimatic changes associated with global warming over the past 50 years have been
documented widely, but physical landscape responses are poorly understood thus far …

Swarm intelligence optimization of the group method of data handling using the cuckoo search and whale optimization algorithms to model and predict landslides

A Jaafari, M Panahi, D Mafi-Gholami, O Rahmati… - Applied Soft …, 2022 - Elsevier
The robustness of landslide prediction models has become a major focus of researchers
worldwide. We developed two novel hybrid predictive models that combine the self …

Landslide susceptibility mapping in Three Gorges Reservoir area based on GIS and boosting decision tree model

F Miao, F Zhao, Y Wu, L Li, Á Török - Stochastic Environmental Research …, 2023 - Springer
As one of the most destructive geological disasters, a myriad of landslides has revived and
developed in the Three Gorges Reservoir area under the combined action of various …

Landslide susceptibility index based on the integration of logistic regression and weights of evidence: A case study in Popayan, Colombia

P Goyes-Peñafiel, A Hernandez-Rojas - Engineering Geology, 2021 - Elsevier
In this paper, we present a suitable integration of discrete and continuous data in a unique
methodology based on systematically collected landslide inventory data. Eleven landslide …

Comparative analysis of machine learning and multi-criteria decision making techniques for landslide susceptibility mapping of Muzaffarabad district

U Khalil, I Imtiaz, B Aslam, I Ullah, A Tariq… - Frontiers in …, 2022 - frontiersin.org
Landslides are natural disasters deliberated as the most destructive among the others
considered. Using the Muzaffarabad as a case study, this work compares the performance of …

Comparison of gradient boosted decision trees and random forest for groundwater potential mapping in Dholpur (Rajasthan), India

S Sachdeva, B Kumar - Stochastic Environmental Research and Risk …, 2021 - Springer
In the drought prone district of Dholpur in Rajasthan, India, groundwater is a lifeline for its
inhabitants. With population explosion and rapid urbanization, the groundwater is being …