A review of hybrid deep learning applications for streamflow forecasting
Deep learning has emerged as a powerful tool for streamflow forecasting and its
applications have garnered significant interest in the hydrological community. Despite the …
applications have garnered significant interest in the hydrological community. Despite the …
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …
sustainability of water resources. The literature has shown great potential for nature-inspired …
Stacked machine learning algorithms and bidirectional long short-term memory networks for multi-step ahead streamflow forecasting: A comparative study
Prediction of river flow rates is an essential task for both flood protection and optimal water
resource management. The high uncertainty associated with basin characteristics …
resource management. The high uncertainty associated with basin characteristics …
Neuroforecasting of daily streamflows in the UK for short-and medium-term horizons: A novel insight
Predicting streamflows, which is crucial for flood defence and optimal management of water
resources for drinking, irrigation, hydropower generation and ecosystem conservation, is a …
resources for drinking, irrigation, hydropower generation and ecosystem conservation, is a …
Near real-time wind speed forecast model with bidirectional LSTM networks
Wind is an important source of renewable energy, often used to provide clean electricity to
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer
Reference evapotranspiration (ET o) is one of the most important and influential components
in optimizing agricultural water consumption and water resources management. In the …
in optimizing agricultural water consumption and water resources management. In the …
[HTML][HTML] Event-based decision support algorithm for real-time flood forecasting in urban drainage systems using machine learning modelling
Urban flooding is a major problem for cities around the world, with significant socio-
economic consequences. Conventional real-time flood forecasting models rely on …
economic consequences. Conventional real-time flood forecasting models rely on …
Computational assessment of groundwater salinity distribution within coastal multi-aquifers of Bangladesh
The rising salinity trend in the country's coastal groundwater has reached an alarming rate
due to unplanned use of groundwater in agriculture and seawater see** into the …
due to unplanned use of groundwater in agriculture and seawater see** into the …
Hybrid intelligence models for compressive strength prediction of MPC composites and parametric analysis with SHAP algorithm
Nowadays, hybrid soft computing technics are attracting the scholars of construction
materials field due to their high adaptability and prediction performances to data information …
materials field due to their high adaptability and prediction performances to data information …
Improving long-term streamflow prediction in a poorly gauged basin using geo-spatiotemporal mesoscale data and attention-based deep learning: A comparative …
Precise long-term streamflow prediction has always been important in the hydrology field,
and has provided essential information for efficient water-resource management and …
and has provided essential information for efficient water-resource management and …