The current research has proposed a novel approach for Flood Hazard (FH) prediction using hybrid Machine Learning (ML) models that integrate ensemble ML models ...
Jan 15, 2024 · An optimum set of Flood Influential Factors (FIFs) was determined using the Simulated Annealing (SA) and Information Gain (IG) FS algorithms.
A novel approach for flood hazard assessment using hybridized ensemble models and feature selection algorithms. Alireza Habibi, Mahmoud Reza Delavar, ...
In this paper, we introduce a novel approach for assessing flood risk through integration of flood hazard mapping using ML techniques and flood vulnerability ...
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To enhance predictive accuracy, we integrate metaheuristic feature selection with ensemble learning models. Initially, fifteen flash flood variables were ...
Mar 14, 2024 · For the purpose of this research, we applied deep learning and machine learning benchmarks in order to prepare flood potential maps at the basin scale.
This study aims to map flood susceptibility in the Qaa'Jahran watersheds located in Dhamar, Yemen, using geoprocessing and computational techniques.
Jul 31, 2020 · Therefore, these hybridized models are a promising, cost-effective method for spatial modeling of urban flood susceptibility and for providing ...
A novel hybrid approach to flood susceptibility assessment based on machine learning and land use change. Case study: a river watershed in Vietnam. May 2022.
Oct 31, 2020 · Extensive literature review shows that various ML algorithms, together with novel ML ensemble methods, were used to map flash flood ...
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