[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review
Develo** accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …
essential for enhancing the planning and management of water resources. Over the past two …
Groundwater level forecasting with machine learning models: A review
Groundwater, the world's most abundant source of freshwater, is rapidly depleting in many
regions due to a variety of factors. Accurate forecasting of groundwater level (GWL) is …
regions due to a variety of factors. Accurate forecasting of groundwater level (GWL) is …
Groundwater level prediction using machine learning algorithms in a drought-prone area
Groundwater resources (GWR) play a crucial role in agricultural crop production, daily life,
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …
and economic progress. Therefore, accurate prediction of groundwater (GW) level will aid in …
Modelling groundwater level fluctuations by ELM merged advanced metaheuristic algorithms using hydroclimatic data
The accurate assessment of groundwater levels is critical to water resource management.
With global warming and climate change, its significance has become increasingly evident …
With global warming and climate change, its significance has become increasingly evident …
Prediction of groundwater level fluctuations using artificial intelligence-based models and GMS
KS Mohammed, S Shabanlou, A Rajabi… - Applied Water …, 2023 - Springer
Groundwater level fluctuations are one of the main components of the hydrogeological cycle
and one of the required variables for many water resources operation models. The …
and one of the required variables for many water resources operation models. The …
Performance improvement of machine learning models via wavelet theory in estimating monthly river streamflow
River streamflow is an essential hydrological parameters for optimal water resource
management. This study investigates models used to estimate monthly time-series river …
management. This study investigates models used to estimate monthly time-series river …
A novel committee-based framework for modeling groundwater level fluctuations: A combination of mathematical and machine learning models using the weighted …
A Mazraeh, M Bagherifar, S Shabanlou… - Groundwater for …, 2024 - Elsevier
Abstract water level (GWL) fluctuations simulation can be divided into three general
categories: Analytical solution, conceptual or physical-based models, and data-based or …
categories: Analytical solution, conceptual or physical-based models, and data-based or …
Groundwater level forecasting in Northern Bangladesh using nonlinear autoregressive exogenous (NARX) and extreme learning machine (ELM) neural networks
DN Fabio, SI Abba, BQ Pham… - Arabian Journal of …, 2022 - Springer
Groundwater resources (GWR) are vital to agricultural crop production, everyday life, and
economic development. As a result, accurate groundwater level (GWL) prediction would aid …
economic development. As a result, accurate groundwater level (GWL) prediction would aid …
Prediction of groundwater level variations using deep learning methods and GMS numerical model
One of the key elements of the hydrogeological cycle and a variable used by many water
resource operating models is the variation in groundwater level (GWL). One of the biggest …
resource operating models is the variation in groundwater level (GWL). One of the biggest …
A hybrid machine learning model for modeling nitrate concentration in water sources
A Mazraeh, M Bagherifar, S Shabanlou… - Water, Air, & Soil …, 2023 - Springer
Nitrate is one of the most dangerous contaminants that can pollute water sources; as a
result, it is always tried to use accurate methods to monitor its quantity. The goal of this study …
result, it is always tried to use accurate methods to monitor its quantity. The goal of this study …