[HTML][HTML] Extreme gradient boosting (Xgboost) model to predict the groundwater levels in Selangor Malaysia
Groundwater levels have been declining recently in Malaysia. This is why, the current study
was aimed to propose an accurate groundwater levels prediction model using machine …
was aimed to propose an accurate groundwater levels prediction model using machine …
Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes
Predictive performance is one of the most important issues for practical applications of
ensemble hydroclimatic forecasts. While different forecasting studies tend to use different …
ensemble hydroclimatic forecasts. While different forecasting studies tend to use different …
A social-ecological coupling model for evaluating the human-water relationship in basins within the Budyko framework
B Wu, Q Quan, S Yang, Y Dong - Journal of Hydrology, 2023 - Elsevier
Correctly understanding the coordinated development between the social economy and the
ecological environment is the key to achieving the sustainable development of river basins …
ecological environment is the key to achieving the sustainable development of river basins …
Neuroforecasting of daily streamflows in the UK for short-and medium-term horizons: A novel insight
Predicting streamflows, which is crucial for flood defence and optimal management of water
resources for drinking, irrigation, hydropower generation and ecosystem conservation, is a …
resources for drinking, irrigation, hydropower generation and ecosystem conservation, is a …
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 …
Stacking ensemble learning models for daily runoff prediction using 1D and 2D CNNs
Y ** reservoirs. Reservoir numerical simulation is the most mature and effective …
A new insight to the wind speed forecasting: robust multi-stage ensemble soft computing approach based on pre-processing uncertainty assessment
In this research, monthly wind speed time series of the Kirsehir was investigated using the
stand-alone, hybrid and ensemble models. The artificial neural networks, Gaussian process …
stand-alone, hybrid and ensemble models. The artificial neural networks, Gaussian process …