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Rahim Barzegar
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Short-term water quality variable prediction using a hybrid CNN-LSTM deep learning model
R Barzegar, MT Aalami, J Adamowski
Stochastic Environmental Research and Risk Assessment 34, 415–433, 2020
3182020
Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models
R Barzegar, E Fijani, A Asghari Moghaddam, E Tziritis
Science of the Total Environment 599 (600C), 20-31, 2017
1972017
Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran
R Barzegar, J Adamowski, AA Moghaddam
Stochastic Environmental Research and Risk Assessment 30 (7), 1797-1819, 2016
1762016
Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms
R Barzegar, A Asghari Moghaddam, R Deo, E Fijani, E Tziritis
Science of the Total Environment 621 (C), 697–712, 2018
1612018
Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of …
E Fijani, R Barzegar, R Deo, E Tziritis, K Skordas
Science of the Total Environment 648, 839-853, 2019
1532019
Coupling a Hybrid CNN-LSTM Deep Learning Model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for Multiscale Lake Water Level Forecasting
R Barzegar, MT Aalami, J Adamowski
Journal of Hydrology, 126196, 2021
1172021
Multi-step water quality forecasting using a boosting ensemble multi-wavelet extreme learning machine model
R Barzegar, AA Moghaddam, J Adamowski, B Ozga-Zielinski
Stochastic Environmental Research and Risk Assessment, 1-15, 2018
1142018
Identification of hydrogeochemical processes and pollution sources of groundwater resources in the Marand plain, northwest of Iran
R Barzegar, A Asghari Moghaddam, E Tziritis, MS Fakhri, S Soltani
Environmental Earth Sciences, 1-17, 2017
1052017
Assessing the potential origins and human health risks of trace elements in groundwater: A case study in the Khoy plain, Iran
R Barzegar, A Asghari Moghaddam, J Adamowski, AH Nazemi
Environmental Geochemistry and Health 41 (2), 981–1002, 2019
1042019
A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer, Iran
R Barzegar, AA Moghaddam, H Baghban
Stochastic Environmental Research and Risk Assessment 30 (3), 883-899, 2016
952016
Combining the advantages of neural networks using the concept of committee machine in the groundwater salinity prediction
R Barzegar, A Asghari Moghaddam
Modeling Earth Systems and Environment 2, 1-13, 2016
932016
Heavy Metal(loid)s in the Groundwater of Shabestar Area (NW Iran): Source Identification and Health Risk Assessment
R Barzegar, A Asghari Moghaddam, S Soltani, E Fijani, E Tziritis, ...
Exposure and Health 11, 251–265, 2019
922019
Assessing the hydrogeochemistry and water quality of the Aji-Chay River, northwest of Iran
R Barzegar, AA Moghaddam, E Tziritis
Environmental Earth Sciences 75 (23), 1-15, 2016
862016
Comparison of machine learning models for predicting fluoride contamination in groundwater
R Barzegar, AA Moghaddam, J Adamowski, E Fijani
Stochastic Environmental Research and Risk Assessment 31 (10), 2705–2718, 2017
852017
Assessment of heavy metals concentrations with emphasis on arsenic in the Tabriz plain aquifers, Iran
R Barzegar, A Asghari Moghaddam, N Kazemian
Environmental Earth Sciences 74, 297-313, 2015
632015
Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones
DK Roy, R Barzegar, J Quilty, J Adamowski
Journal of Hydrology 591, 125509, 2020
622020
Risk assessment and ranking of heavy metals concentration in Iran’s Rayen groundwater basin using linear assignment method
A Rezaei, H Hassani, M Hayati, N Jabbari, R Barzegar
Stochastic Environmental Research and Risk Assessment, 2018
612018
Comparative evaluation of artificial intelligence models for prediction of uniaxial compressive strength of travertine rocks, case study: Azarshahr area, NW Iran
R Barzegar, M Sattarpour, MR Nikudel, AA Moghaddam
Modeling Earth Systems and Environment 2, 1-13, 2016
592016
Characterization of hydrogeologic properties of the Tabriz plain multilayer aquifer system, NW Iran
R Barzegar, A Asghari Moghaddam, M Najib, N Kazemian, J Adamowski
Arabian journal of Geosciences 9, 1-17, 2016
542016
An ensemble tree-based machine learning model for predicting the uniaxial compressive strength of travertine rocks
R Barzegar, M Sattarpour, R Deo, E Fijani, J Adamowski
Neural Computing and Applications 32, 9065–9080, 2020
532020
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