Self-attention (SA) temporal convolutional network (SATCN)-long short-term memory neural network (SATCN-LSTM): an advanced python code for predicting …
Groundwater level prediction is important for effective water management. Accurately
predicting groundwater levels allows decision-makers to make informed decisions about …
predicting groundwater levels allows decision-makers to make informed decisions about …
Hybridization of deep learning, nonlinear system identification and ensemble tree intelligence algorithms for pan evaporation estimation
A reliable pan evaporation (E pan) estimation over a daily scale is vital for sustainable water
and agriculture management, especially for designing water use allocations, irrigation …
and agriculture management, especially for designing water use allocations, irrigation …
Assessment of XGBoost to estimate total sediment loads in rivers
Estimation of total sediment loads is a significant topic in river management as direct
measurement is costly and time-consuming. This study aims not only to use the eXtreme …
measurement is costly and time-consuming. This study aims not only to use the eXtreme …
A novel smoothing-based deep learning time-series approach for daily suspended sediment load prediction
Precise assessment of suspended sediment load (SSL) is vital for many applications in
hydrological modeling and hydraulic engineering. In this study, a smoothed long short-term …
hydrological modeling and hydraulic engineering. In this study, a smoothed long short-term …
Convolutional neural network-support vector machine model-gaussian process regression: a new machine model for predicting monthly and daily rainfall
Rainfall prediction is an important issue in water resource management. Predicting rainfall
helps researchers to monitor droughts, surface water and floods. The current study …
helps researchers to monitor droughts, surface water and floods. The current study …
Convolutional neural network-ANN-E (Tanh): a new deep learning model for predicting rainfall
The prediction of rainfall is essential for monitoring droughts and floods. The purpose of this
paper is to develop a deep learning model for predicting monthly rainfall. The new model is …
paper is to develop a deep learning model for predicting monthly rainfall. The new model is …
Hybrid extreme gradient boosting and nonlinear ensemble models for suspended sediment load prediction in an agricultural catchment
G Gelete - Water Resources Management, 2023 - Springer
In this study, four individual models namely Hammerstein-Weiner (HW), Extreme Learning
Machine (ELM), Long Short-Term Memory (LSTM) and Least Square Support Vector …
Machine (ELM), Long Short-Term Memory (LSTM) and Least Square Support Vector …
[HTML][HTML] Bidirectional Long Short-Term Memory (BILSTM)-Support Vector Machine: A new machine learning model for predicting water quality parameters
Water pollution threatens human health, agriculture, and ecosystems. Accurate prediction of
water quality parameters is crucial for effective protection. We suggest a novel hybrid deep …
water quality parameters is crucial for effective protection. We suggest a novel hybrid deep …
Prediction of future groundwater levels under representative concentration pathway scenarios using an inclusive multiple model coupled with artificial neural networks
Groundwater (GW) plays a key role in water supply in basins. As global warming and climate
change affect groundwater level (GWL), it is important to predict it for planning and …
change affect groundwater level (GWL), it is important to predict it for planning and …
Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in Çoruh River
OM Katipoğlu, V Kartal, CB Pande - Stochastic Environmental Research …, 2024 - Springer
The service life of downstream dams, river hydraulics, waterworks construction, and
reservoir management is significantly affected by the amount of sediment load (SL). This …
reservoir management is significantly affected by the amount of sediment load (SL). This …