[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review
Developing 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 …
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 …
Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas
Predicting water table depth over the long-term in agricultural areas presents great
challenges because these areas have complex and heterogeneous hydrogeological …
challenges because these areas have complex and heterogeneous hydrogeological …
Eye tracking-based diagnosis and early detection of autism spectrum disorder using machine learning and deep learning techniques
Eye tracking is a useful technique for detecting autism spectrum disorder (ASD). One of the
most important aspects of good learning is the ability to have atypical visual attention. The …
most important aspects of good learning is the ability to have atypical visual attention. The …
Flood susceptibility mapping using convolutional neural network frameworks
Flood is a very destructive natural disaster in the world, which seriously threatens the safety
of human life and property. In this paper, the most popular convolutional neural network …
of human life and property. In this paper, the most popular convolutional neural network …
Machine learning algorithms for modeling groundwater level changes in agricultural regions of the US
Climate, groundwater extraction, and surface water flows have complex nonlinear
relationships with groundwater level in agricultural regions. To better understand the relative …
relationships with groundwater level in agricultural regions. To better understand the relative …
Graph neural network for groundwater level forecasting
T Bai, P Tahmasebi - Journal of Hydrology, 2023 - Elsevier
Accurate prediction of groundwater level (GWL) over a period of time is of great importance
for groundwater resources management. Machine learning techniques due to their great …
for groundwater resources management. Machine learning techniques due to their great …
Modeling monthly pan evaporation using wavelet support vector regression and wavelet artificial neural networks in arid and humid climates
Evaporation rate is one of the key parameters in determining the ecological conditions and it
has an irrefutable role in the proper management of water resources. In this paper, the …
has an irrefutable role in the proper management of water resources. In this paper, the …
Past, present and perspective methodology for groundwater modeling-based machine learning approaches
Growing population and rapid urbanization are among the major causes of ground water
level (GWL) depletion. Modeling GWL is considered as tough task as the GWL variation …
level (GWL) depletion. Modeling GWL is considered as tough task as the GWL variation …
An emotional ANN (EANN) approach to modeling rainfall-runoff process
V Nourani - Journal of Hydrology, 2017 - Elsevier
This paper presents the first hydrological implementation of Emotional Artificial Neural
Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall …
Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall …