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 …
Ant-inspired metaheuristic algorithms for combinatorial optimization problems in water resources management
R Bhavya, L Elango - Water, 2023 - mdpi.com
Ant-inspired metaheuristic algorithms known as ant colony optimization (ACO) offer an
approach that has the ability to solve complex problems in both discrete and continuous …
approach that has the ability to solve complex problems in both discrete and continuous …
Runoff forecasting using convolutional neural networks and optimized bi-directional long short-term memory
J Wu, Z Wang, Y Hu, S Tao, J Dong - Water Resources Management, 2023 - Springer
Water resources matters considerably in maintaining the biological survival and sustainable
socio-economic development of a region. Affected by a combination of factors such as …
socio-economic development of a region. Affected by a combination of factors such as …
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 …
Stepwise decomposition-integration-prediction framework for runoff forecasting considering boundary correction
Z Xu, L Mo, J Zhou, W Fang, H Qin - Science of the Total Environment, 2022 - Elsevier
Predicting river runoff accurately is of substantial significance for flood control, water
resource allocation, and basin ecological dispatching. To explore the reasonable and …
resource allocation, and basin ecological dispatching. To explore the reasonable and …
[HTML][HTML] Deep neural network with empirical mode decomposition and Bayesian optimisation for residential load forecasting
In the context of a resilient energy system, accurate residential load forecasting has become
a non-trivial requirement for ensuring effective management and planning strategy/policy …
a non-trivial requirement for ensuring effective management and planning strategy/policy …
Ensemble empirical mode decomposition based deep learning models for forecasting river flow time series
R Maiti, BG Menon, A Abraham - Expert Systems with Applications, 2024 - Elsevier
River flow forecasting is important for flood prediction and effective utilization of water
resources. This study proposed a comprehensive methodology that simultaneously enables …
resources. This study proposed a comprehensive methodology that simultaneously enables …
A combined hydrodynamic model and deep learning method to predict water level in ungauged rivers
G Li, H Zhu, H Jian, W Zha, J Wang, Z Shu, S Yao… - Journal of …, 2023 - Elsevier
Forecasting the water level (WL) of rivers is vital for water resource management. Current
research of WL prediction mainly focuses on gauged sites and further investigation into …
research of WL prediction mainly focuses on gauged sites and further investigation into …
A hybrid data-driven deep learning prediction framework for lake water level based on fusion of meteorological and hydrological multi-source data
Z Yao, Z Wang, T Wu, W Lu - Natural Resources Research, 2024 - Springer
Accurate prediction of lake water level is of great significance for flood prevention, reservoir
scheduling, and ecological protection. However, the change in lake water level is influenced …
scheduling, and ecological protection. However, the change in lake water level is influenced …
Bayesian model averaging by combining deep learning models to improve lake water level prediction
G Li, Z Liu, J Zhang, H Han, Z Shu - Science of The Total Environment, 2024 - Elsevier
Water level (WL) is an essential indicator of lakes and sensitive to climate change.
Fluctuations of lake WL may significantly affect water supply security and ecosystem stability …
Fluctuations of lake WL may significantly affect water supply security and ecosystem stability …