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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 …
Recent advances and new frontiers in riverine and coastal flood modeling
Over the past decades, the scientific community has made significant efforts to simulate
flooding conditions using a variety of complex physically based models. Despite all …
flooding conditions using a variety of complex physically based models. Despite all …
Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as …
Monthly streamflow prediction is very important for many hydrological applications in
providing information for optimal use of water resources. In this study, the prediction …
providing information for optimal use of water resources. In this study, the prediction …
Water quality evaluation and prediction using irrigation indices, artificial neural networks, and partial least square regression models for the Nile River, Egypt
Water quality is identically important as quantity in terms of meeting basic human needs.
Therefore, evaluating the surface-water quality and the associated hydrochemical …
Therefore, evaluating the surface-water quality and the associated hydrochemical …
A physical process and machine learning combined hydrological model for daily streamflow simulations of large watersheds with limited observation data
Physically distributed hydrological models are effective in hydrological simulations of large
river basins, but the complex characteristics of hydrological features limit their application …
river basins, but the complex characteristics of hydrological features limit their application …
Ensemble learning using multivariate variational mode decomposition based on the transformer for multi-step-ahead streamflow forecasting
Accurate streamflow forecasting is critical in the domain of water resources management.
However, the inherently non-stationary and stochastic nature of streamflow poses a …
However, the inherently non-stationary and stochastic nature of streamflow poses a …
[HTML][HTML] An integrated statistical-machine learning approach for runoff prediction
Nowadays, great attention has been attributed to the study of runoff and its fluctuation over
space and time. There is a crucial need for a good soil and water management system to …
space and time. There is a crucial need for a good soil and water management system to …
Fastest‐growing source prediction of US electricity production based on a novel hybrid model using wavelet transform
W Qiao, Z Li, W Liu, E Liu - International Journal of Energy …, 2022 - Wiley Online Library
Electricity is an important indicator for economic development, especially electricity
production (EP), which is electricity industry managers making strategic decisions. There are …
production (EP), which is electricity industry managers making strategic decisions. There are …
An enhanced monthly runoff time series prediction using extreme learning machine optimized by salp swarm algorithm based on time varying filtering based empirical …
Reliable runoff prediction plays a significant role in reservoir scheduling, water resources
management, and efficient utilization of water resources. To effectively enhance the …
management, and efficient utilization of water resources. To effectively enhance the …
Employing machine learning algorithms for streamflow prediction: a case study of four river basins with different climatic zones in the United States
Streamflow estimation plays a significant role in water resources management, especially for
flood mitigation, drought warning, and reservoir operation. Hence, the current study …
flood mitigation, drought warning, and reservoir operation. Hence, the current study …