A systematic literature review on classification machine learning for urban flood hazard map**
The computational expensiveness of the hydrodynamic models and the complexity of the
rainfall-runoff transformation process presents a pressing need to shift to machine learning …
rainfall-runoff transformation process presents a pressing need to shift to machine learning …
Appraisal of flood susceptibility of Hooghly basin, India using Shannon entropy (SE) and fuzzy analytical hierarchy process (FAHP)
Flooding is the most frequent phenomenon that leads to social and economic disruption
worldwide. Effective flood management necessitates an understanding of the spatial …
worldwide. Effective flood management necessitates an understanding of the spatial …
[PDF][PDF] Observation and Geoinformation
SV Razavi-Termeh, A Pourzangbar… - … Journal of Applied …, 2025 - researchgate.net
Managing and controlling costly natural hazards such as floods has been a fundamental
and essential issue for decision-makers and planners from the past to the present. Artificial …
and essential issue for decision-makers and planners from the past to the present. Artificial …
On the application of machine learning into flood modeling: data consideration and modeling algorithm
This article reviews the literature on the application of Machine Learning (ML) to identify
flood-prone areas, covering studies published since 2013. The review focuses on data …
flood-prone areas, covering studies published since 2013. The review focuses on data …
Enhancing accurate prediction of soil permeability coefficients using data-driven approaches for soil and water conservation
L Luo, D Guan, Z Wang - Multiscale and Multidisciplinary Modeling …, 2025 - Springer
Soil permeability coefficient (k) is crucial for water conservation, drainage projects, and
watershed management. In the present study, for modeling k, two powerful white box data …
watershed management. In the present study, for modeling k, two powerful white box data …