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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 …
Study on optimization and combination strategy of multiple daily runoff prediction models coupled with physical mechanism and LSTM
J Guo, Y Liu, Q Zou, L Ye, S Zhu, H Zhang - Journal of Hydrology, 2023 - Elsevier
Accurate prediction of runoff is an important foundation for optimizing water resource
allocation and reservoir scheduling operations. However, due to its complex characteristics …
allocation and reservoir scheduling operations. However, due to its complex characteristics …
Performance comparison of an LSTM-based deep learning model versus conventional machine learning algorithms for streamflow forecasting
Streamflow forecasting plays a key role in improvement of water resource allocation,
management and planning, flood warning and forecasting, and mitigation of flood damages …
management and planning, flood warning and forecasting, and mitigation of flood damages …
Application, interpretability and prediction of machine learning method combined with LSTM and LightGBM-a case study for runoff simulation in an arid area
L Bian, X Qin, C Zhang, P Guo, H Wu - Journal of Hydrology, 2023 - Elsevier
The runoff prediction can provide scientific basis for flood control, disaster reduction and
water resources planning. Due to a large number of uncertainties in runoff prediction, it is …
water resources planning. Due to a large number of uncertainties in runoff prediction, it is …
Ship trajectory planning for collision avoidance using hybrid ARIMA-LSTM models
In maritime transportation, accurate estimation of ship trajectories has a great impact on
collision-free trajectory planning. Previously, many approaches were proposed for ship …
collision-free trajectory planning. Previously, many approaches were proposed for ship …
[HTML][HTML] Coupling the remote sensing data-enhanced SWAT model with the bidirectional long short-term memory model to improve daily streamflow simulations
L **, H Xue, G Dong, Y Han, Z Li, Y Lian - Journal of Hydrology, 2024 - Elsevier
Global climate change has led to an increase in the frequency and scale of extreme weather
events worldwide, and there is an urgent need to develop better-performing hydrological …
events worldwide, and there is an urgent need to develop better-performing hydrological …
Deep learning approach with LSTM for daily streamflow prediction in a semi-arid area: a case study of Oum Er-Rbia river basin, Morocco
Daily hydrological modelling is among the most challenging tasks in water resource
management, particularly in terms of streamflow prediction in semi-arid areas. Various …
management, particularly in terms of streamflow prediction in semi-arid areas. Various …
Simulating runoff under changing climatic conditions: A comparison of the long short-term memory network with two conceptual hydrologic models
Hydrologic models are commonly used to assess climate change impact on water
resources. Several studies have reported that hydrologic models often experience severe …
resources. Several studies have reported that hydrologic models often experience severe …
Impact of COVID-19 on the US Construction Industry as Revealed in the Purdue Index for Construction
Abstract The coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented
impacts (eg, labor shortage, suspension and cancellation of projects, and disrupted supply …
impacts (eg, labor shortage, suspension and cancellation of projects, and disrupted supply …
Improvement of streamflow simulation by combining physically hydrological model with deep learning methods in data-scarce glacial river basin
Robust streamflow simulation at glacial basins is essential for the improvement of water
sustainability assessment, water security evaluation, and water resource management …
sustainability assessment, water security evaluation, and water resource management …