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 …
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 …
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 …
Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR …
Agriculture, meteorological, and hydrological drought is a natural hazard which affects
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
Optimal design and feature selection by genetic algorithm for emotional artificial neural network (EANN) in rainfall-runoff modeling
Rainfall-runoff (rr) modeling at different time scales is considered as a significant issue in
hydro-environmental planning. As a first hydrological implementation, for one-time-ahead rr …
hydro-environmental planning. As a first hydrological implementation, for one-time-ahead rr …
[PDF][PDF] Prediction of the compressive strength of self-compacting concrete using surrogate models
In this paper, surrogate models such as multivariate adaptive regression splines (MARS)
and M5P model tree (M5P MT) methods have been investigated in order to propose a new …
and M5P model tree (M5P MT) methods have been investigated in order to propose a new …
Forecasting groundwater levels using a hybrid of support vector regression and particle swarm optimization
S Mozaffari, S Javadi, HK Moghaddam… - Water Resources …, 2022 - Springer
Forecasting the groundwater level is crucial to managing water resources supply
sustainably. In this study, a simulation–optimization hybrid model was developed to forecast …
sustainably. In this study, a simulation–optimization hybrid model was developed to forecast …
Enhancing robustness of monthly streamflow forecasting model using embedded-feature selection algorithm based on improved gray wolf optimizer
Q Wang, C Yue, X Li, P Liao, X Li - Journal of Hydrology, 2023 - Elsevier
Accurate streamflow prediction plays an essential role in guaranteeing the sustainable
utilization and management of water resources. In recent years, Artificial Intelligence (AI) …
utilization and management of water resources. In recent years, Artificial Intelligence (AI) …
Wavelet coupled MARS and M5 Model Tree approaches for groundwater level forecasting
In this study, two different machine learning models, Multivariate Adaptive Regression
Splines (MARS) and M5 Model Trees (MT) have been applied to simulate the groundwater …
Splines (MARS) and M5 Model Trees (MT) have been applied to simulate the groundwater …
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 …