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. 2025 Apr 7;17(1):1776. doi: 10.4102/jamba.v17i1.1776

TABLE 3.

Top 10 papers with the highest citations.

Title Reference Citation Source title
Flood prediction using machine learning models: Literature review Mosavi et al. (2018) 825 Water
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran Khosravi et al. (2018) 492 Science of the Total Environment
Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method Tehrany, Pradhan and Jebur (2015) 302 Stochastic Environmental Research and Risk Assessment
Survey of computational intelligence as basis to extensive flood management: Challenges, research directions, and future work Fotovatikhah et al. (2018) 292 Engineering Applications of Computational Fluid Mechanics
Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China Zhou et al. (2018) 265 Computers & Geosciences
GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks Tien Bui et al. (2016) 248 Environmental Earth Sciences
A review on early forest fire detection systems using optical remote sensing Barmpoutis et al. (2020) 235 Sensors
A multi-criteria optimisation model for humanitarian aid distribution Vitoriano et al. (2011) 227 Journal of Global Optimization
Tackling climate change with machine learning Rolnick et al. (2023) 204 ACM Computing Surveys
Hybrid artificial intelligence models based on a neuro-fuzzy system and metaheuristic optimization algorithms for spatial prediction of wildfire probability Jaafari et al. (2019) 201 Agricultural and Forest Meteorology

Source: Scopus n.d., Scopus preview - Scopus - Welcome to Scopus, viewed 14 May 2024, from https://www.scopus.com/home.uri