Hybridization of hybrid structures for time series forecasting: A review
Z Hajirahimi, M Khashei - Artificial Intelligence Review, 2023 - Springer
Achieving the desired accuracy in time series forecasting has become a binding domain,
and developing a forecasting framework with a high degree of accuracy is one of the most …
and developing a forecasting framework with a high degree of accuracy is one of the most …
Daily scale streamflow forecasting in multiple stream orders of Cauvery River, India: Application of advanced ensemble and deep learning models
Accurate forecasts of streamflow (Q flow) are crucial for optimal management of water
reservoir systems and preparing for catastrophic events such as floods. Although several …
reservoir systems and preparing for catastrophic events such as floods. Although several …
Spatio-temporal analysis and forecasting of drought in the plains of northwestern Algeria using the standardized precipitation index
Drought is the most frequent natural disaster in Algeria during the last century, with a
severity ranging over the territory and causing enormous damages to agriculture and …
severity ranging over the territory and causing enormous damages to agriculture and …
Hybrid hydrological data-driven approach for daily streamflow forecasting
Hydrological forecasting is key for water resources allocation and flood risk management.
Although a number of advanced hydrological forecasting methods have been developed in …
Although a number of advanced hydrological forecasting methods have been developed in …
Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models
Understanding streamflow patterns by incorporating climate signal information can
contribute remarkably to the knowledge of future local environmental flows. Three machine …
contribute remarkably to the knowledge of future local environmental flows. Three machine …
Remote-sensing-based streamflow forecasting using artificial neural network and support vector machine models
MM Alquraish, M Khadr - Remote Sensing, 2021 - mdpi.com
In this study, we aimed to investigate the hydrological performance of three gridded
precipitation products—CHIRPS, RFE, and TRMM3B42V7—in monthly streamflow …
precipitation products—CHIRPS, RFE, and TRMM3B42V7—in monthly streamflow …
Climate-driven model based on long short-term memory and bayesian optimization for multi-day-ahead daily streamflow forecasting
Y Lian, J Luo, J Wang, G Zuo, N Wei - Water Resources Management, 2022 - Springer
Many previous studies have developed decomposition and ensemble models to improve
runoff forecasting performance. However, these decomposition-based models usually …
runoff forecasting performance. However, these decomposition-based models usually …
Application of integrated artificial neural networks based on decomposition methods to predict streamflow at Upper Indus Basin, Pakistan
Consistent streamflow forecasts play a fundamental part in flood risk mitigation. Population
increase and water cycle intensification are extending not only globally but also among …
increase and water cycle intensification are extending not only globally but also among …
Runoff prediction of irrigated paddy areas in Southern China based on EEMD-LSTM model
S Huang, L Yu, W Luo, H Pan, Y Li, Z Zou, W Wang… - Water, 2023 - mdpi.com
To overcome the difficulty that existing hydrological models cannot accurately simulate
hydrological processes with limited information in irrigated paddy areas in southern China …
hydrological processes with limited information in irrigated paddy areas in southern China …
Solving complex rainfall-runoff processes in semi-arid regions using hybrid heuristic model
AM Al-Juboori - Water Resources Management, 2022 - Springer
In the current research, a hybrid model was proposed to solve the complexity of rainfall-
runoff models in semi-arid regions. The proposed hybrid model structure consists of linking …
runoff models in semi-arid regions. The proposed hybrid model structure consists of linking …