[HTML][HTML] Flash flood susceptibility modelling using soft computing-based approaches: from bibliometric to meta-data analysis and future research directions

G Hinge, MA Hamouda, MM Mohamed - Water, 2024 - mdpi.com
In recent years, there has been a growing interest in flood susceptibility modeling. In this
study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the …

A hybrid intelligent model for spatial analysis of groundwater potential around Urmia Lake, Iran

O Asadi Nalivan, SA Mousavi Tayebi… - … Research and Risk …, 2023 - Springer
The importance of groundwater potential mapping (GWPM) is eminent for the proper
management of underpinning resources. This research applies artificial intelligence-based …

Flood hazard risk assessment based on multi-criteria spatial analysis GIS as input for spatial planning policies in Tegal Regency, Indonesia

AW Sejati, SNAK Putri, S Rahayu, I Buchori… - Geographica …, 2023 - aseestant.ceon.rs
Recent discussions on flood disasters concern the risk factors and causes between nature
and anthropogenic activities. This disaster requires serious handling, which needs to be …

An integrated GIS-based multivariate adaptive regression splines-cat swarm optimization for improving the accuracy of wildfire susceptibility mapping

T Hai, B Theruvil Sayed, A Majdi, J Zhou… - Geocarto …, 2023 - Taylor & Francis
A hybrid machine learning method is proposed for wildfire susceptibility mapping. For
modeling a geographical information system (GIS) database including 11 influencing factors …

Multi-hazard could exacerbate in coastal Bangladesh in the context of climate change

M Rahman, T Shufeng, MSH Tumon… - Journal of Cleaner …, 2024 - Elsevier
Floods and landslides have cascading effects on coastal areas of Bangladesh. This study
aims to develop multi-hazard maps (eg, floods and landslides) for the coastal region, by …

Cutting-Edge strategies for absence data identification in natural hazards: Leveraging Voronoi-Entropy in flood susceptibility mapping with advanced AI techniques

SV Razavi-Termeh, A Sadeghi-Niaraki, F Ali… - Journal of …, 2025 - Elsevier
One of the non-structural methods for flood management is preparing flood susceptibility
mapping (FSM). The performance of flood susceptibility models significantly depends on the …

Predicting solid waste generation based on the ensemble artificial intelligence models under uncertainty analysis

F Ghanbari, H Kamalan, A Sarraf - Journal of Material Cycles and Waste …, 2023 - Springer
Waste is a critical issue the modern world is facing, and its management involves many
imperative parameters with distinct, negative impacts on the environment. From a …

Exploitation of the ensemble-based machine learning strategies to elevate the precision of CORDEX regional simulations in precipitation projection

A Ghaemi, SA Hashemi Monfared, A Bahrpeyma… - Earth Science …, 2024 - Springer
Abstract Multi-model Ensembles (MMEs) are widely used to reduce uncertainties associated
with simulations and projections of GCM/RCM. MMEs combine the results of multiple climate …

Wildfire Risk Assessment Considering Seasonal Differences: A Case Study of Nanning, China

W Yue, C Ren, Y Liang, X Lin, A Yin, J Liang - Forests, 2023 - mdpi.com
Wildfire disasters pose a significant threat to the stability and sustainability of ecosystems.
The assessment of wildfire risk based on a seasonal dimension has contributed to improving …

Review of Flash Flood Susceptibility Modeling Derived from Machine Learning Algorithms with Input Data from Remote Sensing Sources

AO Yusufzai, H Stephen, S Ahmad - World Environmental and Water … - ascelibrary.org
Flash floods can have devastating effects on life and property. Flash flood susceptibility is a
measurement of the likelihood at which flash floods can occur in an area based on the local …