A review of the artificial intelligence methods in groundwater level modeling
T Rajaee, H Ebrahimi, V Nourani - Journal of hydrology, 2019 - Elsevier
This study is a review to the special issue on artificial intelligence (AI) methods for
groundwater level (GWL) modeling and forecasting, and presents a brief overview of the …
groundwater level (GWL) modeling and forecasting, and presents a brief overview of the …
[HTML][HTML] Groundwater quality forecasting modelling using artificial intelligence: A review
This review paper closely explores the techniques and significances of the most potent
artificial intelligence (AI) approaches in a concise and integrated way, specifically in the …
artificial intelligence (AI) approaches in a concise and integrated way, specifically in the …
Reconstruction of missing groundwater level data by using Long Short-Term Memory (LSTM) deep neural network
Monitoring groundwater level (GWL) over long time periods is critical in understanding the
variability of groundwater resources in the present context of global changes. However, in …
variability of groundwater resources in the present context of global changes. However, in …
Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)
While the application of neural networks for groundwater level forecasting in general has
been investigated by many authors, the use of nonlinear autoregressive networks with …
been investigated by many authors, the use of nonlinear autoregressive networks with …
Prediction of effluent concentration in a wastewater treatment plant using machine learning models
Of growing amount of food waste, the integrated food waste and waste water treatment was
regarded as one of the efficient modeling method. However, the load of food waste to the …
regarded as one of the efficient modeling method. However, the load of food waste to the …
A new artificial intelligence strategy for predicting the groundwater level over the Rafsanjan aquifer in Iran
A Sharafati, SBHS Asadollah, A Neshat - Journal of Hydrology, 2020 - Elsevier
This study presents a new strategy to predict the monthly groundwater level with short-and
long-lead times over the Rafsanjan aquifer in Iran using an ensemble machine learning …
long-lead times over the Rafsanjan aquifer in Iran using an ensemble machine learning …
Modeling and uncertainty analysis of groundwater level using six evolutionary optimization algorithms hybridized with ANFIS, SVM, and ANN
In the present study, six meta-heuristic schemes are hybridized with artificial neural network
(ANN), adaptive neuro-fuzzy interface system (ANFIS), and support vector machine (SVM) …
(ANN), adaptive neuro-fuzzy interface system (ANFIS), and support vector machine (SVM) …
Machine-learning algorithms for forecast-informed reservoir operation (FIRO) to reduce flood damages
M Zarei, O Bozorg-Haddad, S Baghban… - Scientific reports, 2021 - nature.com
Water is stored in reservoirs for various purposes, including regular distribution, flood
control, hydropower generation, and meeting the environmental demands of downstream …
control, hydropower generation, and meeting the environmental demands of downstream …
Prediction the groundwater level of bastam plain (Iran) by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS)
S Emamgholizadeh, K Moslemi, G Karami - Water resources management, 2014 - Springer
Prediction of the groundwater level (GWL) fluctuations is very important in the water
resource management. This study investigates the potential of two intelligence models …
resource management. This study investigates the potential of two intelligence models …
The use of NARX neural networks to forecast daily groundwater levels
The lack of information to manage groundwater for irrigation is one of the biggest concerns
for farmers and stakeholders in agricultural areas of Mississippi. In this study, we present a …
for farmers and stakeholders in agricultural areas of Mississippi. In this study, we present a …