A brief review of random forests for water scientists and practitioners and their recent history in water resources
Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …
to gain prominence in water resources applications. However, existing applications are …
Exploring machine learning potential for climate change risk assessment
Global warming is exacerbating weather, and climate extremes events and is projected to
aggravate multi-sectorial risks. A multiplicity of climate hazards will be involved, triggering …
aggravate multi-sectorial risks. A multiplicity of climate hazards will be involved, triggering …
[HTML][HTML] An artificial intelligence model for heart disease detection using machine learning algorithms
The paper focuses on the construction of an artificial intelligence-based heart disease
detection system using machine learning algorithms. We show how machine learning can …
detection system using machine learning algorithms. We show how machine learning can …
Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method
Flash-floods are increasingly recognized as a frequent natural hazard worldwide. Iran has
been among the most devastated regions affected by the major floods. While the temporal …
been among the most devastated regions affected by the major floods. While the temporal …
Evaluating the performance of random forest for large-scale flood discharge simulation
L Schoppa, M Disse, S Bachmair - Journal of Hydrology, 2020 - Elsevier
The machine learning algorithm 'random forest'has been applied in many areas of water
resources research including discharge simulation. Due to low setup and operation cost …
resources research including discharge simulation. Due to low setup and operation cost …
Machine learning techniques for monthly river flow forecasting of Hunza River, Pakistan
The forecast of river flow has high great importance in water resources and hazard
management. It becomes more important in mountain areas because most of the …
management. It becomes more important in mountain areas because most of the …
Earth fissure hazard prediction using machine learning models
Earth fissures are the cracks on the surface of the earth mainly formed in the arid and the
semi-arid basins. The excessive withdrawal of groundwater, as well as the other …
semi-arid basins. The excessive withdrawal of groundwater, as well as the other …
A deep learning approach for hydrological time-series prediction: A case study of Gilgit river basin
Streamflow prediction is a significant undertaking for water resources planning and
management. Accurate forecasting of streamflow always being a challenging task for the …
management. Accurate forecasting of streamflow always being a challenging task for the …
Flood susceptibility prediction using four machine learning techniques and comparison of their performance at Wadi Qena Basin, Egypt
BA El-Haddad, AM Youssef, HR Pourghasemi… - Natural Hazards, 2021 - Springer
Floods represent catastrophic environmental hazards that have a significant impact on the
environment and human life and their activities. Environmental and water management in …
environment and human life and their activities. Environmental and water management in …
Application of machine learning and process-based models for rainfall-runoff simulation in Dupage River basin, Illinois
Rainfall-runoff simulation is vital for planning and controlling flood control events. Hydrology
modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC …
modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC …