Physicochemical parameters data assimilation for efficient improvement of water quality index prediction: Comparative assessment of a noise suppression …
Water quality has a crucial impact on human health; therefore, water quality index modeling
is one of the challenging issues in the water sector. The accurate prediction of water quality …
is one of the challenging issues in the water sector. The accurate prediction of water quality …
Rainfall-runoff modelling using improved machine learning methods: Harris hawks optimizer vs. particle swarm optimization
Y Tikhamarine, D Souag-Gamane, AN Ahmed… - Journal of …, 2020 - Elsevier
Rainfall and runoff are considered the main components in the hydrological cycle.
Developing an accurate model to capture the dynamic connection between rainfall and …
Developing an accurate model to capture the dynamic connection between rainfall and …
A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem
AN Ahmed, T Van Lam, ND Hung, N Van Thieu… - Applied Soft …, 2021 - Elsevier
Hydrological models play a crucial role in water planning and decision making. Machine
Learning-based models showed several drawbacks for frequent high and a wide range of …
Learning-based models showed several drawbacks for frequent high and a wide range of …
Short term rainfall-runoff modelling using several machine learning methods and a conceptual event-based model
The applicability of four machine learning (ML) methods, ANFIS-PSO, ANFIS-FCM, MARS
and M5Tree, together with multi model simple averaging (MM-SA) ensemble method, is …
and M5Tree, together with multi model simple averaging (MM-SA) ensemble method, is …
Using optimized deep learning to predict daily streamflow: A comparison to common machine learning algorithms
From a watershed management perspective, streamflow need to be predicted accurately
using simple, reliable, and cost-effective tools. Present study demonstrates the first …
using simple, reliable, and cost-effective tools. Present study demonstrates the first …
Prediction of surface water total dissolved solids using hybridized wavelet-multigene genetic programming: New approach
Total dissolved solids (TDS) are recognized as an essential indicator of surface water
quality. The current research investigates the potential of a novel computer aid approach …
quality. The current research investigates the potential of a novel computer aid approach …
New double decomposition deep learning methods for river water level forecasting
Forecasting river water levels or streamflow water levels (SWL) is vital to optimising the
practical and sustainable use of available water resources. We propose a new deep …
practical and sustainable use of available water resources. We propose a new deep …
Environmental assessment based surface water quality prediction using hyper-parameter optimized machine learning models based on consistent big data
Prediction of dissolved oxygen (DO) and total dissolved solids (TDS) are of paramount
importance for water environmental protection and analysis of the ecosystem. The traditional …
importance for water environmental protection and analysis of the ecosystem. The traditional …
An adaptive daily runoff forecast model using VMD-LSTM-PSO hybrid approach
X Wang, Y Wang, P Yuan, L Wang… - Hydrological Sciences …, 2021 - Taylor & Francis
To cope with the nonlinear and nonstationarity challenges faced by conventional runoff
forecasting models and improve daily runoff prediction accuracy, a hybrid model-based …
forecasting models and improve daily runoff prediction accuracy, a hybrid model-based …
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 …